2 ND EDITION
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Day Trading with Price Action
Volume IV: Positive Expectancy
Galen Woods
Trading Setups Review
Copyright © 2014-2016. Galen Woods.
PDF eBook Edition
Cover Design by Beverley S.
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Copyright © 2014-2016 by Galen Woods (Singapore Business
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First Edition, 1 September 2014.
Second Edition, 5 April 2016.
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demonstration of concept, for information and education
purposes. They were not necessarily traded live by the author.
U.S. Government Required Disclaimer: Commodity Futures
Trading and Options trading has large potential rewards, but
also large potential risk. You must be aware of the risks and be
willing to accept them in order to invest in the futures and
options markets. Don't trade with money you can't afford to
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or options. No representation is being made that any account
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results.
CFTC RULE 4.41 - HYPOTHETICAL OR SIMULATED
PERFORMANCE RESULTS HAVE CERTAIN LIMITATIONS. UNLIKE
AN ACTUAL PERFORMANCE RECORD, SIMULATED RESULTS DO
NOT REPRESENT ACTUAL TRADING. ALSO, SINCE THE TRADES
HAVE NOT BEEN EXECUTED, THE RESULTS MAY HAVE UNDEROR-OVER COMPENSATED FOR THE IMPACT, IF ANY, OF
CERTAIN MARKET FACTORS, SUCH AS LACK OF LIQUIDITY.
SIMULATED TRADING PROGRAMS IN GENERAL ARE ALSO
SUBJECT TO THE FACT THAT THEY ARE DESIGNED WITH THE
BENEFIT OF HINDSIGHT. NO REPRESENTATION IS BEING MADE
THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFIT
OR LOSSES SIMILAR TO THOSE SHOWN.
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Contents
Chapter 1 - Introduction to Positive Expectancy ...................... 1
1.1 - Definition of Expectancy ............................................ 2
1.2 - Definition of Winning Probability ................................. 3
1.3 - Probability versus Reward-to-Risk............................... 4
1.4 - Beyond Price Action Analysis .................................... 16
1.5 - Conclusion ............................................................. 19
Chapter 2 - Stop-Loss ........................................................ 21
2.1 - Initial Stop-loss ...................................................... 23
2.1.1 - A Method for Losing Small .................................. 25
2.2 - Trailing Stop-losses ................................................ 27
2.2.1 - Price Action Setups ........................................... 29
2.2.2 - Support and Resistance ..................................... 31
2.2.3 - Market Volatility ................................................ 33
2.3 - The Wrong Way to Place Stop-losses ......................... 37
2.4 - Consistency of Stop-losses....................................... 41
2.5 - Conclusion ............................................................. 42
Chapter 3 - Targets ........................................................... 43
3.1 - The Importance of Profit Targets in Day Trading ......... 44
3.1.1 - Trailing Stop-loss .............................................. 44
3.1.2 - Profit Target ..................................................... 44
3.2 - Finding Targets ...................................................... 49
3.2.1 - Support and Resistance ..................................... 49
3.2.2 - Price Thrust Projection ....................................... 53
3.2.3 - Price Channels .................................................. 59
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3.2.4 - Volatility Projection ........................................... 67
3.3 - Exiting with a Reversal Signal .................................. 70
3.3.1 - Anti-climax Pattern ........................................... 71
3.3.2 - Merged Congestion Zone.................................... 74
3.3.3 - Additional Notes................................................ 79
3.4 - Targeting Examples ................................................ 81
3.4.1 - FDAX 10-Minute Example ................................... 82
3.4.2 - ES 10-Minute Example ....................................... 85
3.4.3 - 6J 10-Minute Example ....................................... 89
3.4.4 - CL 3-Minute Example ......................................... 92
3.5 - The Wrong Way to Place Targets .............................. 98
3.6 - Conclusion ............................................................. 99
Chapter 4 - The Meaning of Likely ..................................... 101
4.1 - How to Assess the Probability of Winning ................. 103
4.2 - Conclusion ........................................................... 106
Chapter 5 - Achieving Positive Expectancy.......................... 108
5.1 - The Split Second .................................................. 110
5.1.1 - R2R Indicator ................................................. 113
5.2 - Complete Trading Examples ................................... 117
5.2.1 - CL 4-Minute Example (14 April 2014) ................ 119
5.2.2 - CL 4-Minute Example (1 May 2014) ................... 126
5.2.3 - CL 4-Minute Example (5 May 2014) ................... 133
5.2.4 - CL 4-Minute Example (12 May 2014) ................. 146
5.2.5 - CL 4-Minute Example (15 May 2014) ................. 156
5.2.6 - FDAX 3-Minute Example (8 August 2014) ........... 164
5.2.7 - FDAX 3-Minute Example (31 July 2014) ............. 171
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5.2.8 - FDAX 1-Minute Example (20th November 2015) .. 180
5.3 - Managing Trades for Positive Expectancy ................. 190
5.4 - Conclusion ........................................................... 194
Chapter 6 – The Analytical Cycle ....................................... 196
6.1 - Establish Rules and Guidelines ............................... 199
6.2 - Record Ongoing Analysis ....................................... 202
6.2.1 - Thought Process for Basic Analysis .................... 203
6.2.2 - Written Analysis as a Tool ................................ 205
6.2.3 - Tools for Recording ......................................... 212
6.3 - Classify Trades ..................................................... 214
6.4 - Review Trading Records ........................................ 219
6.4.1 - The Holy Grail................................................. 220
6.4.2 - Measuring Expectancy ..................................... 224
6.4.3 - Computing Drawdown (for Position Sizing) ......... 232
6.4.4 - Improving Expectancy ..................................... 239
6.5 - Refine Trading Rules and Guidelines........................ 253
6.6 - Conclusion ........................................................... 254
Chapter 7 - A Risk-Based Approach to Trading .................... 255
7.1 - Identifying Risks ................................................... 256
7.2 - Risk Management Card .......................................... 260
7.3 - Financial Risk ....................................................... 263
7.3.1 - Trading Capital ............................................... 263
7.3.2 - Living Expenses .............................................. 265
7.3.3 - Currency Risk ................................................. 267
7.4 - Operational Risk ................................................... 269
7.4.1 - Trading Computer ........................................... 271
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7.4.2 - Electricity ....................................................... 273
7.4.3 - Internet Connection ........................................ 274
7.4.4 - Broker ........................................................... 276
7.4.5 - Trading Platform ............................................. 280
7.4.6 - Execution Process ........................................... 281
7.4.7 - Trading Environment ....................................... 283
7.4.8 - Minimise Risk by Keeping It Simple ................... 284
7.5 - Psychological Risk ................................................. 285
7.5.1 - Psychological Foundation ................................. 289
7.5.2 - Practical Strategy ............................................ 292
7.5.3 - The Final Determinant ..................................... 303
7.6 - Integration of Risks .............................................. 303
7.7 - Conclusion ........................................................... 305
Chapter 8 - End of the Beginning ...................................... 307
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Chapter 1 - Introduction to Positive
Expectancy
The expectancy of a trading setup refers to the expected
outcome of taking that setup many times over a long period of
time. The sole aim of every trader is to take setups with positive
expectancy in order to accumulate profits. Otherwise, your
trading capital will be depleted in a matter of time.
Having a positive expectancy is also referred to as having a
trading edge. Conceptually, it is akin to a casino’s edge. Over a
large number of bets, the casino expects to make a profit at the
gamblers’ expense.
As profit-driven traders, positive expectancy is everything.
The difference between us and the casinos is that their edge is
rooted rock solid in statistics. They have rigged the games in
their favour, and they know it. They can even prove it. As for
us, we are trying to rig the game, not quite knowing if we have
succeeded. It is a much tougher play for traders.
So, if you can get over the legal issues and possibly moral
qualms, I suggest that you open a casino rather than day trade
futures.
When it comes to trading, there are numerous topics covering
strategies, indicators, setups, entries, exits, risk management,
psychology, software, hardware, and many others. Ultimately,
these pieces should fit together to help you take trading setups
that exhibit positive expectancy.
Positive expectancy is the single most important concept in
trading. Hence, it is essential that every trader has a thorough
understanding of it and see how the different parts of a strategy
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Chapter 1 - Introduction to Positive Expectancy
come together to highlight opportunities with positive
expectancy. While the concept of having a trading edge is
covered in many trading books, most of them do not give it the
attention it deserves.
The earlier volumes taught you how to analyse market bias and
trading setups. However, they did not show you how to trade,
because nobody can trade without understanding the concept of
positive expectancy.
To learn how to trade, read on.
In this first chapter, we will break down the concept of
expectancy into concrete aspects that we can examine and
improve with respect to each trading opportunity. The ultimate
purpose is, of course, positive expectancy for each trade we
take.
1.1 - Definition of Expectancy
To this end, we cannot be content with the one-line basic
definition mentioned above. Expectancy is more than a fluffy
trading concept. It is a statistical concept. To achieve positive
expectancy, we have to understand it statistically.
If you did not enjoy your mathematics classes, do not fear.
There are only three ingredients.



Probability of winning a trade = W
Reward of a trade = R
Risk of a trade = L
Expectancy = ( W x R ) – [ ( 1 – W ) x L ]
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Chapter 1 - Introduction to Positive Expectancy
Both intuition and mathematics tell us that to maximise
expectancy, we need to:



Maximise the probability of winning a trade (W)
Maximise the reward of a trade (R)
Minimise the risk of a trade (L)
It seems like there are three distinct steps to finding great
trading opportunities.
1. Find a high probability trade.
2. Place our target far away to maximise profit.
3. Place our stop-loss near to minimise risk.
That sounds simple.
Unfortunately, the above recipe is wrong. The greater
misfortune is perhaps the large number of traders with this
erroneous understanding.
To uncover the correct approach, you need to understand the
true meaning of winning a trade and the inter-relationships
between the winnings odds, our target, and our stop-loss.
1.2 - Definition of Winning Probability
Many traders discuss the probability of winning a trade as
though it is independent of its potential reward and risk.
That understanding cannot be any further from the truth and is
a very dangerous idea. Any discussion of the probability of a
winning trade is flawed if it does not incorporate its potential
reward and risk. It is important to comprehend why.
The first step is to understand what it means when we say we
win a trade. It means that the trade results in profits.
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Chapter 1 - Introduction to Positive Expectancy
Let’s assume that each time we enter the market, we place a
target limit order and a stop-loss order, and we do not adjust
them.
It follows that for a trade to be profitable, the market must hit
our target before hitting our stop-loss. If our stop-loss level is
hit first, then our trade results in losses and not profits.
Hence, the probability of winning a trade is the probability of the
market hitting our target price before hitting our stop-loss point.
This is why the probability of winning a trade is not independent
of its target and stop-loss. Thus, we must integrate them into a
single thought process. As mentioned, a useful way to formulate
the winning probability of a trade is the “probability that the
market will hit our target before hitting our stop-loss”.
PROBABILITY OF WINNING
Probability that the market will hit our
target before hitting our stop-loss
This definition offers great insight. It shows clearly that the
probability of winning a trade is dependent on how well we set
our target and stop-loss.
1.3 - Probability versus Reward-to-Risk
The next step is to find out exactly how our targets and stoplosses are related to our winning probability.
For clarity, let’s start with a completely random market. A
random market implies that, assuming there is no slippage and
commissions, the long run outcome of any trading strategy is
breakeven.
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Chapter 1 - Introduction to Positive Expectancy
Let us establish a long position in this hypothetical market. We
place a sell limit order above our entry price as our target and
concurrently place a sell stop order below our entry price as a
stop-loss. Our target and stop-loss are equidistant from our
entry price.
For illustrative purpose, let’s assume that both the target and
stop-loss are 10 ticks away from our entry price as shown in
Figure 1-1.
Target (50%)
10 ticks
Entry price
10 ticks
Stop-loss (50%)
Figure 1-1 Equidistant target and stop-loss
Since the market is random, the probability that it will move up
10 ticks is the same as the probability of moving down 10 ticks.
Basically, the probability of either scenario is 50%. This means
that over the long run and over many such trades, 50% of the
trades will make us 10 ticks each, and 50% of the trades will
incur 10 ticks of losses each. Since the profit per winning trade
is the same as the loss per losing trade, we will end up in a
breakeven position. (Assuming that that there are no slippages
and commissions.)
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Chapter 1 - Introduction to Positive Expectancy
Now, let’s consider a trade with a 20-tick target and 10-tick
stop-loss. What are the odds of this trade being profitable? Is it
still 50%?
If it is, according to our expectancy formula, we expect to make
5 ticks per trade (0.5 x 20 – 0.5 x 10). When we say we expect
to make 5 ticks a trade, we mean that our average profit per
trade over a large number of trades is 5 ticks.
Wow, fantastic. Simply by using a larger target, we have
managed to squeeze some money out of a random market.
Is that possible?
Absolutely not. It is impossible to make money from trading a
random market over the long run.
By placing our target further from our entry price, a random
market will no longer churn out winning trades and losing trades
with equal probability.
Instead, the market will have a lower probability of hitting our
target first and a higher probability of hitting our stop-loss first.
This is because the distance between our target and our entry
price is larger than the distance between the stop-loss and our
entry price.
The 50-50 probability applies only when the target and the stoploss are at the same distance away from our entry price (i.e.
when our reward-to-risk ratio is 1). When we push our target
further to 20 ticks away and maintain our stop-loss at 10 ticks
away, our reward-to-risk ratio increases to 2.
Thus, the probability of the market hitting our target order
before hitting our stop-loss order decreases to approximately
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Chapter 1 - Introduction to Positive Expectancy
33.3%. The probability of the market hitting our stop-loss
before reaching our target increases to roughly 66.6%.
Figure 1-2 illustrates this change in probability.
Target (33.3%)
20 ticks
Entry price
10 ticks
Stop-loss (66.6%)
Figure 1-2 Lower winning probability for higher reward-to-risk ratio
How do we know this? How did we get the probabilities of
33.3% and 66.6%?
Recall that the market we are talking about here is random and
the outcome of any trading strategy over the long run is
breakeven.
Simply put, it indicates an expectancy of zero. By plugging the
value of zero into the expectancy formula, we can work out the
relationship between the probability of winning a trade, and the
target and stop-loss of a trade, in a random market.
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Chapter 1 - Introduction to Positive Expectancy
Expectancy = 0 (Random market)



W – Winning probability
R – Reward
L - Risk
(W x R) – [(1 - W) x L] = 0
W x R = L x (1 - W)
R / L = (1 – W) / W
We plotted a graph of Winning Probability (W) against Rewardto-Risk (R/L) using this equation in Figure 1-3. It reveals an
important relationship. In a random market, the probability of
winning decreases as our reward-to-risk ratio increases.
Figure 1-3 Decreasing probability with increasing reward-to-risk ratio
This graph illustrates the definite breakeven outcome in a
random market without trading costs like commissions and
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Chapter 1 - Introduction to Positive Expectancy
slippage. The expectancy of every trade is zero and falls on this
line.
The relationship depicted in Figure 1-3 is intuitive. Achieving the
target is necessary for winning a trade. The further the target,
the harder it is for the market to achieve it. Hence, the further
we place our target, the higher the reward, and the lower the
probability of winning the trade. Conversely, if our target is
near, our probability of winning increases.
Another necessary condition for our trade to succeed is that the
market must not hit our stop-loss before hitting our target.
Thus, tighter stops lower our winning probability because the
market has a higher chance of hitting them. Wider stops are
less likely to be hit by the market. Hence, the further we place
our stop-loss, the larger the risk, and the higher our winning
probability.
When we combine these two lines of thought, we conclude that
the higher the reward-to-risk ratio, the lower the winning
probability. This inevitable trade-off between the winning
probability and the reward-to-risk ratio is an essential trading
concept.
This random market marks our theoretical start point. Now, let’s
move on to considering the same relationship in real markets.
Does the relationship described above hold true for the real
financial markets that we intend to trade?
The efficient market hypothesis is relevant for this discussion. I
am not going to expound on the full-fledged theory, and will just
present a short explanation before we move on.
Basically, the hypothesis states that markets are efficient at
absorbing price-sensitive information. The more efficient they
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Chapter 1 - Introduction to Positive Expectancy
are in doing so, the harder it is for anyone to make money from
the market.
The underlying explanation is very logical. If there is a trading
strategy that works, everyone will jump in and trade with that
strategy. In doing so, the trading edge of that strategy is
eroded.
For instance, let’s consider the January effect1 which is the
tendency for stock prices to rise in January each year. This is
purportedly due to income tax reasons. The trading strategy to
take advantage of the January effect is to buy stocks near the
end of the year and sell them in January after the stock prices
has risen.
However, if everyone employs the same strategy, then they
would all buy near the end of the year. By doing so, they push
up the prices. As a result, the difference between their cost
basis and the eventual (supposedly higher) price in January
narrows. Their potential profit diminishes. If the market is
perfectly efficient, this impact will be so pronounced that
January effect simply ceases to exist.
In a perfectly efficient market, all information is reflected in its
price and movements cannot be anticipated. Thus, all
movements are random. In that case, the relationship in Figure
1-3 would hold.
Everyone who is trying to make money from the market
believes that financial markets are not entirely efficient. They
believe that inefficiencies of varying degrees exist in the market.
Some detractors of the efficient market hypothesis go as far as
to say that the hypothesis is wholly wrong and completely
useless.
First documented by Sidney B. Wachtel in his 1942 paper “Certain Observations on
Seasonal Movements in Stock Prices”.
1
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Chapter 1 - Introduction to Positive Expectancy
I do not agree with this extreme view. The efficient market
hypothesis does make sense. Its underpinnings are logical and
rational. Hence, I believe that it is difficult to make money from
trading the market and profitable opportunities are fleeting. The
generally high failure rates of traders and the underperformance
of most fund managers prove this point.
At the same time, to believe that markets are completely
efficient is naïve.
Thus, a realistic view is that it is possible, although challenging,
to make money from predicting market movements.
The relationship in Figure 1-3 holds true in financial markets
most of the time. However, at times, the market exhibits a kink
in the relationship that offers positive expectancy. Those kinks
represent the trading opportunities we are looking for.
Figure 1-4 illustrates where these positive expectancy
opportunities lie.
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Chapter 1 - Introduction to Positive Expectancy
Positive Expectancy
Negative Expectancy
Figure 1-4 Positive expectancy region on the right of the curve
Recall that the curve represents zero expectancy. Note that
traders do not start on the line of zero expectancy. Due to
trading costs like commissions and slippage, all traders start in
the negative expectancy region.
Our job as traders is to focus on getting on the right side of the
line where we find trading setups with positive expectancy.
These setups can be the result of a higher probability or higher
reward-to-risk ratio or both.
A reward-to-risk ratio of 1 paired with a winning probability of
0.5 (50%) produces zero expectancy. If there is a chance to
enter the market with a reward-to-risk ratio of 1.5 and
probability of 0.5, do we take it? Yes, because it has a better
reward-to-risk ratio than a zero expectancy trade. It carries
positive expectancy.
Great, we know where we want to be - on the right side. But
how do we get there?
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Chapter 1 - Introduction to Positive Expectancy
The key factor that causes opportunities to open up on the right
side of the zero expectancy line is the market bias. The market
bias denotes a higher tendency of the market to move in one
direction, either up or down. If the market has no bias, then it is
random. In that case, there is no money to be made. If the
market has a bias and we manage to decipher it, then there is
money to be made.
Thus, if we get the market bias right, we have managed to
squeeze through to the right side of the graph. This is why we
devoted the entire Volume II to the art of figuring out the
market bias.
This is also why the market bias is our foremost consideration
when we look at any market we intend to trade. If we are
unsure of the market bias, we are unsure if we are on the left or
right side of the graph in Figure 1-4. When we are unsure, we
should not trade.
“He will win who knows when to fight and when not to fight.”
Sun Tzu, The Art of War
However, even after we confirm the market bias, we cannot
enter the market until we are able pinpoint an exact entry with
a clear reward-to-risk ratio and an acceptable probability.
To define our reward-to-risk ratio, we need to find a reliable
trading setup aligned with the market bias. It will give us our
entry price and stop-loss level. The difference between them is
our risk.
Concurrently, we must figure out where to put our target by
examining the market support/resistance and by employing
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Chapter 1 - Introduction to Positive Expectancy
target projection techniques. The difference between our target
price and our entry price is our reward.
Then, we can finally put our reward and risk together to find out
our reward-to-risk ratio.
How about the probability of winning?
Recall that the probability of winning refers to the probability of
the market reaching our target before hitting our stop-loss. It
follows that the probability of winning depends on how well we
select our stop-loss and target.
We need a stop-loss that the market is likely to stay away from.
This means that we need to find a high quality trading setup.
Then, we need a target that the market is likely to move to,
which means that we need to find a magnetic target level that
draws the market towards it.
Accordingly, to maximise the winning probability, we need to
examine how we select our target and stop-loss, and if they are
reliable.
Summing up the above, we get the correct approach to finding
trading opportunities as shown in Table 1-1.
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Chapter 1 - Introduction to Positive Expectancy
No. Task
Purpose
1
Determine the market bias
Open up the possibility of
positive expectancy
2
Find a reliable stop-loss point
Define risk
3
Find a reliable target level
Define reward
4
Determine how likely it is for
the market to hit the target
before hitting the stop-loss
Define probability
Calculate expectancy
Evaluate if the trade
offers positive
expectancy
5
Table 1-1 Correct trading approach
We enter the market only if the setup offers positive
expectancy. Let’s take a look at our progress with respect to this
trading approach.
Assessing the market bias is the subject matter of Volume II.
Return to it if you are still unsure of the techniques for
uncovering the market bias.
Items 2 to 5 lay out the roadmap for the first part of this
volume.
In Chapter 2, you will learn that a high quality trading setup will
provide a reliable stop-loss. As we have already discussed the
attributes of a high quality setup in Volume III, we will devote
our time to learning about alternative stop-loss techniques and
their implications.
In Chapter 3, you will pick up techniques to identify reliable
targets. We will rely heavily on our earlier discussion on support
and resistance, in particular the different types of swing pivots
and the Congestion Zone. We will also talk about the importance
of using target limit orders in day trading.
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Chapter 1 - Introduction to Positive Expectancy
In Chapter 4, we will embrace the fuzziness of deriving the
probability of winning. We ask ourselves what is the likelihood
that the market will hit our target before hitting our stop-loss?
This is where we decipher the inner workings of our mind in an
attempt to arrive at a quantified probability of a successful
trade.
In Chapter 5, we will combine risk, reward, and probability using
the expectancy formula to decide if a trading opportunity is
worth taking. This chapter also contains comprehensive
examples to bring you through the entire trading process, from
evaluating the market bias to deriving the expectancy of a
trade. These important examples serve to reinforce everything
we have learned and show how they fit together to produce
profitable trading prospects.
1.4 - Beyond Price Action Analysis
The second part of this volume, from Chapter 6 onwards, moves
beyond price action analysis. Our trading approach creates our
trading edge. Beyond that, we need to focus on two things.
First, we work on improving our trading edge or expectancy. We
will deal with this in Chapter 6 in which we will focus on keeping
good records of our trades and learn how to analyse them to
improve our trading performance.
Next, we ensure that we are adequately prepared to exploit the
positive expectancy of our trading strategy. In Chapter 7, we
will discuss the three main risks that might affect our ability to
trade.
First, we must avoid financial risks, in particular the risk
of ruin. Every trading strategy suffers drawdowns, including
those with positive expectancy. For instance, you have a trading
strategy that would cause you to lose $1,000 before making
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Chapter 1 - Introduction to Positive Expectancy
$5,000 for each traded contract. That is a great strategy with
positive expectancy. However, can you start trading it with
$500?
Clearly not, because if you start trading with $500, there is a
good chance that you will run out of money before you can
realise the expected profit of $5,000. You will need at least
$1,000, preferably more, for each contract you trade.
The basic idea here is that you must have enough money to
rough it out before you realise the positive expectancy of your
trading strategy. It is about surviving until you make it.
Hence, we will work on ensuring that you have enough trading
capital for the results of a positive expectancy strategy to
manifest, and finding out the position size you can trade given
your trading capital.
Second, we must be prepared for contingencies during
the actual trading process. We will identify a list of possible
risks that might affect our ability to trade according to our
analysis. Basically, we try to answer the question of what might
go wrong during our trading session.



Will the Internet connection drop?
Will our broker be unavailable?
Will your wireless mouse run out of battery?
We will implement a framework for reviewing and handling such
risks.
In doing so, we will establish standard trading procedures and
controls to govern our actual trading process. This is essential to
ensure that we are able to take advantage of the good trades
we identify.
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Chapter 1 - Introduction to Positive Expectancy
We must know what trading aids to place on our charts and
which screen to pay attention to at which point in time. When a
trading opportunity with positive expectancy arises, you must
know exactly which button to click and be able to click it without
a family member barging into your room.
Focusing on the things that might go wrong helps us to drill
down to the tiniest detail in our trading process and hammer
them out clearly. Only then, we are able to act without
hesitation or interference when a trading opportunity arises.
Third, we need to manage the risk of emotions running
amok. We will face a trader’s worst psychological demons.
Very often, taking negative expectancy trades is not fatal, as
long as the good trades more than make up for them. What is
fatal is giving in to the fear and greed and other mental demons
that cause you to neglect all the trading principles you know.
That will lead you will ignore the trading rules you’ve set for
yourself and trade excessively. To realise the positive
expectancy of our trades, we must keep our emotions, chiefly
fear, in check.
It is important to understand that managing these three types
of risks merely enable us to take positive expectancy trades.
Managing them does not create a trading edge. It merely
preserves our trading edge, if we indeed have one.
Having a lot of money will not help you make more money if
you do not have a trading edge. You’ll just survive longer as a
losing trader. (Okay, with a lot a lot of money, you might create
a trading edge to make money. But most ways of doing that are
illegal.)
Maintaining iron-clad discipline to take negative expectancy
trades will just deplete your trading capital in an orderly fashion.
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Chapter 1 - Introduction to Positive Expectancy
However, these aspects of trading are almost as important as
the analytical aspects because without them, you are unable to
realise the results of your market analysis. And if you do not
pay attention to them, you may end up eroding your trading
edge. In all, these factors are necessary but not sufficient for
trading profitably.
1.5 - Conclusion
The most important concept in this chapter is the definition of
the probability of winning.
It is the probability of the market reaching our target price
before hitting our stop-loss.
This single concept enjoins our entry, stop-loss, and target, and
is extremely instructive on the right way to find solid trading
setups.
Taking trades with positive expectancy is our sole purpose.
Every single aspect of our trading plan must bring us closer to
doing so.
Chapter 1 to 5 of this volume is on how to find trades. Chapter 6
and 7 discusses the business and psychological aspects of
trading. I’ve chosen to combine them in one final volume to
highlight an often neglected fact – trading is more than just
your trading strategy.
Your strategy, process, and psychology fit together to produce
the elusive positive expectancy.
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Chapter 1 - Introduction to Positive Expectancy
POSITIVE EXPECTANCY

Look for trades with positive
expectancy

Understand that the winning
probability of a trade depends on its
stop-loss and target

Prepare yourself financially,
operationally, and mentally
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Chapter 2 - Stop-Loss
Stop-loss orders are orders placed to limit our loss in the event
that the market moves against us. Typically, they are placed as
stop orders after our market entry.
Stop-loss is not a popular topic. Some new traders are not even
aware of the concept of stop-losses, and many traders often
avoid talking about it. This is because stop-losses are associated
with losing. It is never good for business (and ego) to discuss
too much about losing in the market. At best, these traders
treat stop-losses as an invisible but necessary evil. If we adopt
this attitude, we will miss exploring a crucial aspect of trading.
Of course, I do not like to lose as well. However, losing is such
an important theme in trading that we should pay it proper
attention. To a large extent, trading is about losing right, and
losing small. And stop-losses are our best tool to achieve this.
LOSING MONEY CORRECTLY
Trading is about losing right, and losing
small
How do we lose right?
Losing right refers to losing as part of a set of consistent trades
with positive expectancy. Within a set of trades with positive
expectancy, we expect overall gain.
However, we are also aware that not all trades will be profitable.
There will be losing trades. These losing trades are desirable
because they accompany winning trades that surpass them in
aggregate results.
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Chapter 2 - Stop-Loss
Hence, to ensure that we lose right, we must focus on taking
positive expectancy trades. As long as we are doing so, even if
we are stopped out, we know that we have lost desirably.
How do we lose small?
Small is a relative concept. It is relative to the size of the
potential profit. The smaller the potential loss, the larger
reward-to-risk ratio. It is also relative to the winning probability.
Hence, to find out how small is enough, we need to plug our
potential loss into the expectancy formula. This will be done in
Chapter 5.
Stop-losses help us lose correctly and lose small. It also means
that a stop-loss serves two competing aims.
It should help us lose small and limit our losses.2 This implies
that a tight stop-loss is desirable.
However, it should help us lose right. To do so, it must allow
enough room for a good trade to unfold and hit the profit target
despite market fluctuations. This means that the stop-loss
should be placed at a safe distance away.
Given these considerations, setting a stop-loss is delicate
business. The ideal stop-loss level is the tightest one that offers
enough room to accommodate reasonable movement against
your trading position.
What is considered reasonable movement against our position?
Stop-loss orders are generally not guaranteed. They take the form of stop orders.
When the market hits the specified price, the stop order turns into a market order to be
executed immediately. However, the exact execution price depends on market
conditions. Thus, although stop-loss orders help to limit our losses, they do not
guarantee the amount we stand to lose.
2
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Chapter 2 - Stop-Loss
I do not have a straightforward answer for you. But I can tell
you that it depends on three factors: price patterns,
support/resistance, and volatility.
In the following sections, we will examine the impact of each
factor on our stop-loss placement.
2.1 - Initial Stop-loss
The probability of winning a trade is the probability that the
market will reach our target before hitting our stop-loss.
The stop-loss plays an important role in our search for high
probability trades. We need to find a reliable initial stop-loss
level for each trading opportunity.
What is a reliable stop-loss?
In the context of a long trade, a reliable stop-loss level is one
that the market is more likely to stay above. For a short trade,
the market tends to stay below a reliable stop-loss level. In
addition, a reliable stop-loss level is one that signals that our
analysis is wrong when the market hits it.
Recall that in our price action framework, we always place the
stop-loss order a tick below the setup bar for a long trade and a
tick above the setup bar for a short trade.
This is because our setups are based on price points where we
believe buying or selling pressure will take over and push the
market to our advantage. Hence, if our trading premise is right,
the opposite extreme of the setup bar is a reliable stop-loss
point.
Thus, the reliability of our stop-loss depends on the quality of
our trading setup. This is a concept I have highlighted in the
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Chapter 2 - Stop-Loss
introduction of the previous volume. The analysis of the market
bias and trading setups covered in the last two volumes will help
us to find reliable stop-loss points.
Finding a good trading setup gives us an entry point. More
importantly, it gives us a reliable stop-loss level.
To find reliable stop-loss points, look for high quality setups in
the direction of the market bias. The quality of the setup
depends on the support/resistance areas, confluence of price
patterns, and the form of the setup. (Refer to Volume III
Chapter 19 for details.)
Re-entry equivalent setups also offer quality trading
opportunities. (Refer to Volume III Chapter 12 for details.)
Price action setups, market volatility, and support/resistance
affect how we place our initial stop-loss. However, I recommend
using price action setups for initial stop-loss placement as it
offers a direct way to link our entry conditions with our exit
strategy.
So far, we have been using a price action setup as our basis for
placing initial stop-loss. We consistently place our stop-loss a
tick below a long setup bar or a tick above a short setup bar.
Moreover, we do not adjust it regardless of the price action that
follows after our entry.
This is passive trade management, which refers to keeping our
stop-loss and target constant regardless of how the trade
progresses. The implication of passive trade management is that
we maintain a fixed reward-to-risk ratio for each trade. Having a
fixed reward-to-risk ratio simplifies the calculation of expectancy
and makes it easier for us to assess if a trade has positive
expectancy.
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Chapter 2 - Stop-Loss
2.1.1 - A Method for Losing Small
I mentioned that we want to lose correctly and small. So far, we
have been focusing on finding reliable setup bars and placing
our stop-loss around them. This helps us to lose correctly.
To lose small, I have a simple method for you.
Take only narrow range setup bars.
To define a narrow range bar, use a long-term moving average
of bar range as a benchmark. Any bar with a range below the
benchmark is a narrow range bar. (We will use this definition
again when we learn to trail stops using market volatility later.)
What is a long-term moving average of bar range?
It is a moving average that uses bar range (bar high – bar low)
as its input. It is not a standard indicator on most trading
platforms.3 However, if your trading platform allows you to nest
indicators, you can set it up easily. Simply set bar range as the
input of your moving average indicator.
For the look-back period of the moving average, use the total
number of bars in five trading sessions. The moving average will
then include five complete sessions and account for any day-ofthe-week nuances in volatility.
For instance, in an hourly chart showing 24-hour trading
sessions, we would use the average range of the last 120 price
bars (24 hourly bars x 5 trading sessions).
Narrow range bars are favourable setup bars for two reasons.
It is not the Average True Range (ATR) indicator found on most platforms. The
difference is that the ATR accounts for gaps between price bars. You may use ATR for
swing trading, but stick to a simple moving average of bar range for day trading.
3
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Chapter 2 - Stop-Loss
First, as our trade risk is determined by the bar range, a narrow
range setup bar means a lower trade risk.
Next, assuming that the market continues to move with the
average volatility (bar range), it produces a better reward-torisk ratio. Generally, a narrow range setup bar in a volatile
market is likely to enjoy a higher reward-to-risk ratio.
These reasons explain why there is a variety of price patterns
surrounding narrow range bars like the NR4 and NR7.4
(If you use the R2R indicator to project minimum targets, you
may choose to hide the targets for wide range bars by
specifying the appropriate look-back period. Learn more in
Chapter 5.1.1 - R2R Indicator.)
There are a few important things to note when implementing
this technique.
First, narrow range bars in isolation do not produce a trading
edge. Hence, while you should aim to take narrow range setup
bars, you should not take a trade simply because the setup bar
has a narrow range.
Always assess the quality of the setup first. Then, use the bar
range as a filter. If the bar range is too wide and the trade
entails too much risk, skip it.
Next, this technique is an extreme measure to lose small. When
applied rigidly, it might cause you to skip many high quality
trades that happen to have wide range setup bars. Hence, weigh
your decision against the quality of the trading setup. If the
trading setup is fantastic, a wide range bar might be acceptable.
Refer to Toby Crabel’s Day Trading with Short Term Price Patterns and Opening Range
Breakout. Click here for more information.
4
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Chapter 2 - Stop-Loss
If the trading setup is of average quality, insist on having a
narrow range setup bar.
Finally, in your attempt to make use of narrow range bars to
control risk, be aware that narrow range bars often occur in
congested markets. Hence, if you see too many narrow range
bars too frequently, consider avoiding the possibly congested
price action instead of jumping into the market.
2.2 - Trailing Stop-losses
In contrast to the passive trade management that we have been
employing, some traders prefer to manage their trading
positions actively. They adjust their stop-loss according to the
price action that unfolds after their entry to try to improve their
trades. This practice is known as trailing stop-loss.
Trailing a stop-loss always refers to moving the stop-loss in the
direction of the trade. You can move the stop-loss closer to the
entry price to lower the trade risk. You can also move it to lock
in profits once the market has moved in your favour by a
reasonable margin.
However, under no circumstances should a stop-loss be moved
against the direction of the trade. For instance, in a long trade,
the stop-loss order should never be moved to a lower price
level. It should only be shifted upwards.
As long as the stop-losses are adjusted based on price analysis,
trailing stop-loss is a valid technique. However, it should only be
used by experienced and proficient traders. This is because
there are two significant drawbacks that might bring new
traders more harm than good.
First, it is generally more challenging to control your emotions
after you enter a position. You might be able to remain calm
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Chapter 2 - Stop-Loss
and conduct solid analysis leading up to your trade entry. But
after you have taken a financial interest in the market, your
emotions and cognitive biases tend to flare up. Your perspective
becomes anchored to your entry price. Your mind is fixated on
not becoming a loser. It becomes a lot harder to analyse the
market clearly. Without proper analysis, you will not be able to
adjust your stop-loss with sound reasoning. You end up
adjusting your stop-loss emotionally, and not analytically.
Even if you are able to control your emotions when it comes to
trailing stop-losses, you will still need to deal with a technical
difficulty.
With simple passive targets and stop-losses, calculating the
expectancy of a trade is straightforward as we have a fixed
reward-to-risk ratio for each trade. However, with trailing stoplosses, our reward-to-risk ratio fluctuates throughout the trade.
This varying reward-to-risk ratio has a profound impact on our
trade's expectancy.
We might get stopped out with a smaller loss or with a smaller
gain. By adjusting the stop-loss, we also inevitably affect the
probability of winning. If we trail the stop-loss too tightly, we
decrease the probability of winning. If we trail it too widely, we
increase the probability of winning but might decrease the size
of our reward.
Undeniably, trailing stop-loss complicates the expectancy of a
trade and its impact is difficult to grasp. Only experienced
traders who are confident that their active trade management is
adding value should adjust stop-losses during a trade.
To find out if trailing stop-losses is adding value to your trading
performance, you need to keep detailed trading records that
include your trade management decisions and rationale.
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Chapter 2 - Stop-Loss
If you are game for trailing stop-losses, you may employ the
following techniques to do so.
2.2.1 - Price Action Setups
Since we place our initial stop-loss based on a price action
setup, there is no reason why we should not adjust them
according to subsequent new setups.
If a new long trading setup forms while we are in a long trade,
we have the option of moving our stop-loss order upwards to
just beneath the setup bar of the new long setup. This will
tighten our stop-loss and decrease our potential trade risk.
Similarly, a new short trading setup in a short trade gives us the
option of shifting our stop-loss down.
Conceptually, trailing a stop-loss based on a trading setup is no
different from entering a new trading setup. We are merely
taking into account a setup that occurred when we are already
in the market. In fact, if you are not trading your maximum
number of contracts, other than shifting the stop-loss order, you
can also add to your position according to the new setup.
Thus, in deciding if you should trail a stop-loss according to a
new trading setup, consider the quality of the setup. A good
setup implies a good stop-loss level. Hence, evaluate the quality
of the new setup. The better the quality of the setup, the
stronger the case for trailing your stop-loss.
Figure 2-1 shows an example of trailing a stop-loss down in a
short trade as a bearish Pressure Zone setup occurred.
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Chapter 2 - Stop-Loss
2. Stop-loss order almost hit
3. Bearish
Pressure Zone
4. Trailed
stop-loss here
1. Bearish Congestion
Break-out Failure;
shorted here
Figure 2-1 Trailing a stop-loss down with a bearish Pressure Zone
1. The market bias was bearish. Hence, we sold a tick below this
bar due to the bearish Congestion Break-out Failure. As usual,
we placed a stop-loss order a tick above the high of the setup
bar.
2. After moving down for two bars, the market reversed up and
went right up to the high of our setup bar, which was just a tick
below our stop-loss order. Although that caused some traders to
hold their breath for a moment, price soon fell.
3. During the descent, a bearish Pressure Zone formed. This
Pressure Zone formed right after price was rejected from the
high of our original setup bar. In addition, the last bar of the
Pressure Zone was a powerful bear trend bar.
Hence, we adjusted the stop-loss order down to just above the
last bar of the Pressure Zone. This new stop-loss level helped to
lock in a 2-tick profit without stifling the setup’s profit potential.
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Chapter 2 - Stop-Loss
2.2.2 - Support and Resistance
We can find support and resistance with swing pivots, trend
lines, and Congestion Zones. Technically, we can trail our stoplosses according to any type of support and resistance in long
and short trades respectively. However, basic and tested pivots
are usually less reliable for trailing stop-losses.
Hence, I recommend the following price action formations for
the purpose of trailing stop-losses.


Valid pivots
Pivots with Congestion Zones
The first method simply trails the stop-loss order a tick below a
valid low for long trades, and a tick above a valid high for short
trades. (If you are not sure what a valid pivot is, refer back to
Volume II. Valid pivot is the most reliable type of pivot and
often acts as major support/resistance.)
The second method is an effective trailing stop-loss technique
that uses Congestion Zones to find reliable pivots as stop-loss
points. Basically, for long trades, we wait for price to clear
above a Congestion Zone before bringing our stop-loss to the
nearest pivot low below the Zone. For short trades, after price
clears below a Congestion Zone, we bring the stop-loss to the
nearest pivot high above the Zone.
This technique is demonstrated in a long trade in Figure 2-2.
The dotted boxes in Figure 2-2 represent Congestion Zones.
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Chapter 2 - Stop-Loss
1. Bullish Congestion
Break-out Failure;
bought here
3. Similar logic
but with a bullish
setup too
2. This bar cleared above the Congestion
Zone, so we adjusted the stop-loss to the
nearest pivot below the Zone
Figure 2-2 Using Congestion Zones as a guide for trailing stop-loss
1. To trade the bullish Congestion Break-out Failure, we bought
a tick above this setup bar. As usual, our stop-loss was placed a
tick below it.
2. The higher bar was the first that cleared above the
Congestion Zone. It confirmed the Zone as a support area.
Hence, we shifted the stop-loss order to the pivot low just below
the Congestion Zone.
3. Again, a similar situation emerged and we trailed the stoploss order higher. In addition, in this case, we had another
reason for trailing the stop-loss because the Congestion Zone
also led to a bullish Congestion Break-out Failure.
In many cases, you will find that trailing stop-losses using
support/resistance produces similar results as using a trading
setup. This is not surprising as our trading setups are designed
to find short-term reliable stop-loss points, which are essentially
finer and more precise support/resistance points.
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Chapter 2 - Stop-Loss
2.2.3 - Market Volatility
The two methods we just discussed rely on price action
formations. The market must form swing pivots or other price
action patterns before we have a basis to adjust our stop-losses.
However, at times, the market might move quickly in the
direction of your trade without offering any suitable price action
formation for trailing stop-losses. When that happens, consider
the use of volatility stop-losses.
The underlying concept is that with a given volatility, a
directional market is unlikely to retrace more than a certain
distance. Volatility is typically measured by the average bar
range or standard deviation. Using volatility as a basis for
trailing stop-losses makes sense.
Chuck LeBeau popularised the idea of placing stop-losses based
on market volatility with his Chandelier Stops. It is a stop
placement technique based on the average true range (ATR).
The ATR is a way to compute average bar range while taking
into account the gaps between bars. The Chandelier Stop is then
placed and trailed as a multiple of the ATR behind price
movement.
As gaps are uncommon within intraday time frames, day traders
do not need to compensate for gaps. In fact, be careful when
using the ATR in intraday charts. This is because the ATR will
take the gap between trading sessions into account, resulting in
an overstated value.
Hence, the volatility stop-loss technique I am about to introduce
uses the average bar range, which is a simple moving average
of bar range (high-low), and not ATR. Let’s call this technique
the Wide Range Bar Trail.
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Chapter 2 - Stop-Loss
Before we proceed, let’s define a wide range bar.
If you have been observing a particular market within the same
time frame for some time, you can easily tell if a bar’s range is
wide or narrow without the help of indicators.
For a technical definition, I suggest using a long-term moving
average of bar range as a benchmark. Any bar with a range
above the long-term average is a wide range bar. For the lookback period of the moving average, use the number of bars in
five trading sessions. The moving average will then include five
complete sessions and account for any day-of-the-week nuances
in volatility.
For instance, the 60-minute chart of 6E futures in Figure 2-3
has 24 bars in each 24-hour trading session. Hence, we will take
the 120-period (24 x 5) moving average of bar range as our
benchmark. Any bar with a range that is higher than the
benchmark is a wide range bar.
In a long trade, once a price bar closes above the high of a
bullish wide range bar, we shift our stop-loss to a tick below the
wide range bar. In a short trade, once a price bar closes below
the low of a bearish wide range bar, we shift our stop-loss to a
tick above the wide range bar.
Figure 2-3 demonstrates the Wide Range Bar Trail method in a
bullish context. The bullish wide range bars are highlighted in
yellow.
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Chapter 2 - Stop-Loss
D
1
1. Closing above
bullish wide range bars
C
1
B
1
A
1
B
1
D
1
C
1
3. When price closes
above these bars, the
stop-loss can be
adjusted higher again
2. And their corresponding
trailing stop-loss level
A
1
Figure 2-3 Using the Wide Range Bar Trail for a long position
1. Each letter above the price bars indicates a close above a
bullish wide range bar. Each close was a signal for us to tighten
our stop-loss according to the Wide Range Bar Trail.
2. The corresponding trailing stop-loss levels are marked below
the price bars. You can match each trigger signal to its
associated stop-loss level using the letter labels. (E.g. after bar
close A, trail to stop-loss level A)
3. We would not adjust the stop-loss order to a tick below these
two bullish wide range bars until a price bar closes above them.
Figure 2-4 shows a Wide Range Bar Trail example within the
context of a short trade. The bearish wide range bars are
highlighted in yellow.
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Chapter 2 - Stop-Loss
1. First trail
A
1
3. Choose the tightest
stop-loss option
B
1
A
1
2. The first close below four
bearish wide range bars
B
1
Figure 2-4 Wide Range Bar Trail for a short position
1. The example above follows the same labelling convention as
the previous one (Figure 2-3). Level A was the first trailing stoploss in this chart.
2. This bar closed below four bearish wide range bars at once,
offering us with four possible new stop-loss levels.
3. Under such circumstances, choose the tightest stop-loss
level.
However, this is not a strict rule. Choosing the tightest option is
conservative. If you would like to be more ambitious and allow
more room for the market to wiggle, use the furthest option.
The Wide Range Bar Trail offers a sensible stop-loss level for
two reasons. For ease of explanation, let’s assume that we are
in a long position.
First, a bullish wide range bar represents powerful bullish
strength. When the market closes above it, it is a decisive signal
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that the market is following through with the bullish force.
Hence, for a price action trader, the low of the wide range bar is
a logical stop-loss level.
Second, as we place our stop-loss below a wide range bar, we
are providing our setup with above average range as breathing
room. This space serves to accommodate potential trend
retracement before the market moves further in our favour.
Thus, this trailing stop-loss method combines both volatility and
price action considerations.
Before you start to use the Wide Range Bar Trail, make sure you
go through the two notes that follow.
First, trailing stop-losses using price patterns, and support and
resistance is more reliable. This is why you should employ the
Wide Range Bar Trail only when price is moving quickly in your
favour without offering suitable support and resistance for stoploss placement.
Next, if the wide range bar has an exceptionally wide range and
extremely high volume, it might be a sign of price exhaustion.
In a bull market, it means that all the buyers have bought. No
one is left to buy, and a bearish reversal is imminent. In a bear
market, it means that traders who want to sell have sold. No
one is left to sell, and a bullish reversal would follow.
In such cases, it is prudent to exit immediately using a market
order, instead of tightening your stop-loss order.
2.3 - The Wrong Way to Place Stop-losses
Earlier, we tried to define the ideal stop-loss, which is the
tightest possible stop-loss that offers just enough room to
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accommodate reasonable movement against our position. We
defined it to guide us as we explore the various techniques for
placing stop-losses.
However, in real trading, we can only dream of having the
perfect stop-loss and can never pinpoint it. Generally, the
tighter the stop-loss order, the more likely it is for the market to
hit it. Thus, market reality forces us to choose between small
trade risk and low probability of our stop-losses being hit. You
either lose small and frequent, or lose big and seldom.
We have examined the different techniques of placing stoplosses and adjusting them. Trade management is a very
personal issue because it occurs at a stage where the trader is
already financially committed to the market.
Some traders prefer to trail stop-losses closely to control their
trade risk while facing higher chance of being stopped out.
Others prefer to keep their stop-losses away by a conservative
margin. For these traders, while their average risk per trade is
higher, they are more likely to obtain a higher win rate.
Regardless of your preference, you should employ an analytical
mind in trade management, using the techniques described
above.
Stop-losses come in many flavours including initial and trailing
stops, pattern stops, volatility stops, support/resistance stops
and many others that lie beyond our scope. However, we can
simplify them into two types that matter.
The first type uses market analysis as its basis. The second type
arises from our emotions. Adhere to a simple principle. Stoplosses arising from your analysis are acceptable, but those
prompted by your emotions are not.
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EMOTIONS
Avoid placing and adjusting stop-losses
based on your emotions
We have preferences when it comes to managing our paper
profits and losses. However, do not let your preference manifest
itself emotionally.
The prime example is the breakeven stop-loss. It refers to a
stop-loss that is placed at the trade entry price so as to ensure
that the trade will never become a loser. A breakeven stop-loss
is the favourite tool of traders who prefer to lose small and
frequent. They think that breakeven stop-losses will achieve
their objective of cutting losses.
However, by placing breakeven stop-losses, they are blatantly
giving in to the anchoring bias. They anchor their perspective to
their entry price. Since a breakeven stop-loss is placed only to
avoid losses, it is driven by a fear of losing money, rather than
by the market’s price action. The market does not care if the
trade makes or loses money, but the trader does. This disparity
between the market reality and the trader’s mind-set affects the
trader’s performance. Placing and adjusting stop-losses based
on emotions is never a good idea.
If you prefer to lose small and to lock in profits whenever
possible, you should wait for the market to offer a natural price
action development before trailing your stop-losses. Placing
stop-losses in the middle of nowhere without considering either
price action or volatility is a recipe for strangling the positive
expectancy in your trades.
An example of an emotional stop-loss is shown in Figure 2-5.
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Chapter 2 - Stop-Loss
1. Bearish Anti-climax
in a bull trend
4. Using pivot lows for trailing
stop-losses is the way to go
2. Long Anxiety
Zone setup bar
3. If we had moved the stop-loss to
breakeven without an analytical
basis, we would be stopped out here
Figure 2-5 A breakeven stop-loss has no price action basis
1. Price rose with a bearish Anti-climax pattern. Given the
bullish market, we did not take the short setup. Instead, we
waited for it to fail and lead us into an eventual long Anxiety
Zone setup.
2. The setup bar came in the form of a bullish reversal bar. We
bought as price broke above it. Our initial stop-loss was a tick
below the setup bar.
3. The market gave us three consecutive bullish bars which
were enough to prompt the impatient trader to place a
breakeven stop-loss at our entry price. However, the entry
price had little significance as a support level. Hence, that
decision was not rooted in analysis, but in emotions.
This bearish outside bar hit the breakeven stop-loss to the tick.
4. The correct way to lock in our profits was to wait for at least
a basic pivot low before shifting our stop-losses upwards. As it
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Chapter 2 - Stop-Loss
losses that managed to lock in profits while still allowing the
market to continue rising.
Here, we used a basic pivot low to trail our stop-loss order. As
support levels, basic pivot lows are not as reliable as valid lows.
Nonetheless, it is much better to use a basic low to trail a stoploss order, rather than trailing it to your entry price which has
no technical significance.
2.4 - Consistency of Stop-losses
While you are free to employ any stop-loss placement method,
you must make sure that it is consistent with your trading
strategy, especially in the case of trailing stop-loss.
It is a simple concept. Generally, the more ambitious you are
with respect to setting your trade target, the larger the margin
you should provide for your trade to wiggle.
Practically, the questions that you need to consider are:


How do you expect the trade to pan out?
Is your stop-loss consistent with your expectations?
Let’s say you are a scalper aiming for very small profits. For
profitable trades, you would expect price to hit your target
swiftly without any pullbacks. Hence, you should be very
aggressive in tightening your stop-loss.
On the other hand, if you entered the market believing that it
was the start of a new trend and hence placed an ambitious
profit target, you should be less aggressive when it comes to
tightening the stop-loss. You cannot reasonably expect the
market to cover a large distance without any pullbacks. Hence,
your stop-loss strategy should account for this and leave greater
room for possible pullbacks. For example, you should avoid
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using basic pivots for trailing stop-losses and stay with the more
significant valid pivots instead.
As you should have gathered by now, consistency is a major
theme in this book. Every aspect of a trading strategy should be
consistent. Only then, we can aim for long-term sustainable
profits.
2.5 - Conclusion
With a trading setup, we know where to enter and where to
exit. Thus, we know how much we stand to lose. We have
derived an important input of the expectancy formula - risk.
For beginners, stick with the default method of placing stoplosses based on price patterns. In addition, adopt passive trade
management. Once you gain sufficient experience, you can
experiment with trailing stop-losses.
As for active trade management (active adjustment of stoplosses and targets), we will discuss more about the thought
process governing it in Chapter 5.
STOP-LOSSES

Stick to passive initial stop-loss using
trading setups when starting out

Use price patterns, support and
resistance, and volatility to place your
stop-loss

Do not set stop-losses emotionally
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Chapter 3 - Targets
As opposed to the chapter on stop-losses, this chapter is a
happy one about taking profits and making money.
A profit target is placed with the aim of exiting the market with
a profit once the market has moved in our favour for a
reasonable distance.
Target orders are usually limit orders placed above the market
price for long positions and below the market price for short
positions.
While many traders agree that a stop-loss order is absolutely
necessary to control our trade risk, they differ in their opinions
regarding the need for target orders. This is because while a
stop-loss is the only reliable way to limit our potential loss,
there are several ways to secure our potential profit.




Exit with a trailing stop-loss (as discussed in last chapter)
Exit with a fixed target (static limit order)
Exit with a moving target (shifting limit order like with the
price channel I will introduce later)
Exit with a reversal signal (market order)
As you can see, traders can choose to take their profits with
stop-loss orders, target limit orders, or simply market orders.
There is a perpetual argument over the best way to exit a trade.
This argument is pointless because nobody needs the best way.
We just need a consistent method that makes sense and
ensures positive expectancy.
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3.1 - The Importance of Profit Targets in
Day Trading
Let’s take a closer look at exiting with trailing stop-loss and
target limit orders as they are two of the more common exit
methods among day traders.
3.1.1 - Trailing Stop-loss
In the last chapter, we saw examples of trailing stop-losses with
price patterns and support/resistance levels to lock in profits.
From the perspective of profit-taking, trailing-stops have the
following characteristics.



Locks in profits by trailing behind favourable market
movement
Allows profits to run if the stop-loss is placed
appropriately
Gives some paper profits back to the market
3.1.2 - Profit Target
The implications of using target limit orders are different. Target
limit orders by definition exit at the most favourable price
attained during the trade and do not give back paper profits.
Figure 3-1 shows how we use a limit order to exit at our profit
target.
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Chapter 3 - Targets
3. Measured
move target
based on
this upthrust
4. Sold here with
a limit order
2. Bought here
1. Long Congestion
Break-out Failure
Figure 3-1 Using a limit order to exit at our profit target
1. This chart shows a long Congestion Break-out Failure.
2. We bought as the market broke above the setup bar.
3. We projected our target using a measured move based on an
earlier bullish thrust. We will discuss this technique later in this
chapter.
4. Price rose swiftly to hit our sell limit order placed just below
the projected target.
In this case, it appeared to be an ideal target as price formed a
double top around that price level before collapsing back to our
entry price level.
However, a drawback of using target orders is that we decide
how much profit we can take from the market rather than
letting the market decide. In other words, we fail to let profits
run and miss out on windfall profits when the market blasts
away in the direction of our trade.
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Figure 3-2 reveals the price action that follows our exit in Figure
3-1. It shows how the market continued to rise higher without
hitting our stop-loss level.
2. The market
continued to rise
1. We exited here
Figure 3-2 What we missed out
1. This was our earlier exit.
2. The market continued to rise. We could have earned around
three times more if we did not exit with the profit target.
So, which method is better? Trailing stop-loss or fixed target
limit order?
Many traders repeat this mantra, “Cut your losses short, and let
your profits run.” Thus, conventional wisdom seems to advocate
using trailing stop-losses which have the ability to let our profits
run.
Using a trailing stop-loss is definitely beneficial for traders
operating within the daily time frame and above. Let's take
swing traders for instance. They enter the market with the
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intention of capturing the next market swing over the next few
days to the next couple of weeks. However, if the trade takes on
favourable momentum, they can choose to extend the duration
of their trade and trail their stop-loss prudently5. In this case,
they can potentially capture a huge chunk of a prolonged
secular trend. That is a very attractive proposition.
However, this proposition is not present within the context of
day trading. By definition, day traders exit before the end of a
trading session. Hence, our profit potential is limited by the
range of each trading session. We need to bear this in mind
when we decide on our exit technique.
Day traders try to capture market movements within intraday
time frames and must exit before the session ends. Hence, even
with a prudent trailing stop-loss strategy, there is a clear limit to
our profit potential compared to that of higher time frame
traders. The opportunity to catch the next major market swing
does not exist for day traders.
Thus, the incentive for employing trailing stop-loss for intraday
trading is diminished. Within this context of limited profit
potential, we should aim for realistic and modest targets. Along
with this line of reasoning, I strongly suggest that day traders
use target orders to secure their profits.
TARGET LIMIT ORDERS
Day traders should use target orders
due to a limited time horizon
The decision to use target orders stems from our need to exit by
the end of a trading session. This limit on our holding period
5
Assuming that they are not trading short-term options that have high time decay.
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Chapter 3 - Targets
places a major obstacle to windfall profits. Hence, for strict day
traders who exit by the end of each session, target orders are
sensible.
However, for traders operating within intraday time frames but
hold positions across trading sessions, trailing stop-loss makes
as much sense for them as for swing traders. This is because
these traders are effectively longer term traders operating
within intraday time frames in order to fine-tune their entries.
They are not interested in lower day trading margins or in
avoiding overnight risk. Consequently, they are able to raise the
limit on their profit potential. Many forex traders operating
within the 4-hour time frame fall within this category.
In addition, a profit target enhances discipline which is critical
for day traders making swift decisions. When we exit a position
with a target limit order, we know the exact price point where
we are taking profits off the table. We have a plan. And having a
plan is far more important than having the perfect plan. Without
an exit plan, we get confused and emotional. We become timebombs.
Remember that we do not need the perfect exit. First, there is
no perfect exit. Next, we can afford to leave some money on the
table and walk away, as long as the trading opportunity offers
positive expectancy in totality.
Despite the fact that a trailing stop-loss is not the ideal tool for
day traders to take profit, we are not precluded from using
trailing stop-loss in conjunction with profit targets. We can
certainly use the former to reduce risk and lock in some profits,
while maintaining a pre-set profit target within the market. The
key point is that day traders should always have a working
profit target in the market.
Now that we have established the importance of profit targets in
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day trading, let’s look at the different ways to find reliable
targets.
3.2 - Finding Targets
A reliable target is a price level that seems magnetic and
attracts price to it. How does a price level become magnetic?
A bullish market will rise until it hits a resistance level. Hence,
as a bullish market rises up to the resistance, it seems as
though it is attracted to the resistance level. A more accurate
description is that the market was bullish and rose, until it was
resisted. The resistance was more of a roadblock than a
magnet. Likewise, in a bearish market, price tends to fall until it
is hindered by a support area.
Thus, our aim is to find these potential roadblocks and use them
as our targets. To do this, we need to map out the
support/resistance levels of the market to find out where prices
might stall. In addition, we can also apply target project
techniques to find suitable targets.
3.2.1 - Support and Resistance
As the market rises, price tends to stall at resistance areas.
Hence, for a long trade, a target right below a resistance area is
ideal. A falling market tends to stall at support areas. Thus, for
a short trade, our target should be placed right above a support
area.
In application, we should mark out the support and resistance
areas around our entry price and observe the ease of market
movement around these levels. It is usually sufficient to mark
out the three support/resistance levels closest to the market
price. This is because it is unlikely for price to bust through
three resistance/support levels without a significant pullback.
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The useful support/resistance areas include:



Swing pivots
Congestion Zones
High/low/close of trading sessions
What is the basis of our observation?
We look out for support/resistance areas.
Then, how do we find reliable targets?
The basic idea is to examine the degree of support and
resistance between the entry price and the potential target.
The likelihood that the market will hit a target in a long trade is
inversely related to the amount of resistance between the entry
price and the proposed target price. The higher the amount of
resistance in between the two levels, the lower the likelihood of
the market reaching the target.
Let’s say we are considering a long trade, and there are five
resistance levels above the current market price. The nearest
resistance level is the most reliable target. The next higher
resistance level is a less probable target as the market has to
defeat the first resistance before it can reach it. Following this
logic, each of the further resistance represents a less reliable
target.
Similarly, the likelihood that the market will hit a target in a
short trade is inversely related to the amount of support
between the entry price and the proposed target price. The
higher the amount of support in between the two levels, the
lower the likelihood of the market hitting the target.
Avoid plotting so many support/resistance levels that
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meaningful analysis becomes challenging. I usually only
consider at most the past 30 days of price action when I map
out the support/resistance areas.
Figure 3-3 shows an example of how to analyse support levels
to find a good profit target.
1. Short Pressure
Zone setup bar
4. Low of
previous session
2. Previous
extreme low
3. Merged Congestion Zone
5. Session low two sessions ago
Figure 3-3 Mapping out the support areas for a short trade
1. As we consider taking the short Pressure Zone setup, we
checked out the support areas below for a potential profit
target. For now, let’s focus on the part of the chart to the left of
the setup bar.
2. The nearest support was the last extreme low of the current
market descent. Basically, it was the lowest pivot low formed
just before the market pulled back up to form the bearish
Pressure Zone. These previous extremes are usually the most
reliable profit targets as was the case in this example.
3. Moving down, the next lower support was a merged
Congestion Zone from two sessions ago. As a prior zone of
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Chapter 3 - Targets
significant price congestion, it was clearly a potential support
area.
4. Furthermore, the low of the previous session was also within
the Congestion Zone. Together, they provided a confluence of
potential targets that enhanced the reliability of using that price
level as a profit target. We will explore the concept of
confluence in greater detail later in this chapter.
5. The most ambitious target on this chart was the support
provided by the session low from two sessions ago. This was
because for the price to hit a target placed here, the market had
to first push through the thick merged Congestion Zone.
Based on the above, the low of the previous session offered the
most suitable target. This is due to the confluence with the
Congestion Zone which is an effective price magnet even in
isolation.
Now, let’s look at the price action after the short Pressure Zone
setup.
The Congestion Zone was obviously a key price area that
contained the market for a couple of swings before sending it on
its way up again.
Although the market fell through the Congestion Zone and hit
the furthest target we marked at the session low two sessions
ago, you must realise that this target level was indeed a less
probable target than the ones above or within the Congestion
Zone.
Support/resistance areas represent a vital factor in setting
targets. In our targeting process, we should accord the greatest
weight to support/resistance. The target projection techniques
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using price formations and volatility we will look at below serve
to complement the support/resistance structure.
3.2.2 - Price Thrust Projection
The support/resistance framework for working out targets is
only useful when we are able to rely on the price action of the
recent past to project support/resistance. For instance, in the
example in Figure 3-3, we were able to project support levels
based on the price action from the past two sessions.
However, when the market is moving into a price range where it
has not treaded through recently, we are unable to rely on past
price action to project support/resistance areas. In such cases,
target projection techniques are useful.
Target projection techniques refer to using the magnitude of a
recent significant price movement or formation as the basis for
projecting targets.
Even when there are support/resistance areas to guide our
targeting process, projection techniques still offer a valuable
second opinion.
Among the price formations that can be used for projecting
targets, I find that price thrusts work the best for a trend
trading framework. The following explains how to find potential
targets using price thrusts.
For projecting bullish targets,
1. Look for a series of bullish bars that contains at least two
bull trend bars. The ideal thrust comprises at least three
consecutive bullish bars with at least two bull trend bars.
(For the definition of a trend bar, refer to Volume III
Chapter 4.)
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2. Measure the distance between the lowest opening price
and the highest closing price of the thrust.
3. Project the same distance from the highest close of the
thrust to obtain the target level.
Figure 3-4 shows an example of a bullish target projection in the
ES 10-minute time frame.
4. Projected target hit here
3. Project the
same distance
Highest closing price
1. Three-bar
bullish thrust
2. Measure the distance between
Lowest opening price
Figure 3-4 Projecting a bullish target with an upthrust
1. We selected the first three-bar bullish thrust of the session.
2. We were only interested in the body of the thrust. Hence, we
marked out the lowest opening price and the highest closing
price of the thrust to measure the distance between them.
3. Then, we project the measured distance from the highest
close of the bullish thrust to get our target.
4. The projected target turned out to be around the highest
price of the trading session, offering an excellent target for any
long trades initiated in the earlier part of the session.
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For projecting bearish targets,
1. Look for a series of bearish bars that contains at least two
bear trend bars. The ideal thrust comprises at least three
consecutive bearish bars with at least two bear trend
bars.
2. Measure the distance between the highest opening price
and the lowest closing price of the thrust.
3. Project the same distance from the lowest close of the
thrust to obtain the target level.
Figure 3-5 shows an example of projecting bearish targets
within the NQ 5-minute time frame.
Highest opening price
1. Nine-bar
bearish thrust
2. Measure the distance between
Lowest closing price
3. Project the
same distance
4. Projected target hit here
Figure 3-5 Projecting a bearish target using a strong downthrust
1. The market started with a three-bar bullish thrust before
changing into the reverse gear with a nine-bar downthrust.
2. We measured the distance between the opening price of the
first bar in the downthrust and the closing price of the last bar.
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Chapter 3 - Targets
3. Then, we projected the same distance downwards starting
from the last close of the downthrust for the profit target.
4. The projected target price caught the low of the day, as
closely as we could have asked for.
This trading session truly demonstrates the power of target
projection using price thrusts. Let’s take a closer look at the
other bearish thrusts in this trading session as pointed out in
Figure 3-6.
1. Nine-bar
bearish thrust
2. Five-bar downthrust
3. Three-bar
downthrust
Figure 3-6 Bearish price thrusts suitable for target projection
The targets projected using these three downthrusts are shown
in Figure 3-7.
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These 3 solid lines are
the projected targets
Figure 3-7 Confluence of three targets pinpointed the session low
The solid lines mark out the targets projected using the three
downthrusts. (Dotted lines mark out the start and end of each
thrust.) This is a remarkable example showing the effectiveness
of price thrust projections, especially when they cluster around
the same price level. When you get clustered projections like
this, you must pay attention, as they provide extremely reliable
price targets.
Please do not take this example as proof that price thrust
projections are the perfect price targets. If you select random
thrusts for target projection, you will find that many projections
do not work as well and at times do not work at all.
Nonetheless, when the market bias is clear, firm price thrusts in
its direction offer a solid basis for projecting targets. The
following types of price thrusts project particularly reliable
targets.

The first strong thrust that leads to a change of the
market bias
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
A break-out thrust from a prolonged sideways market
I do not know exactly why target projection techniques work,
but they seem to work often enough for me to include them in
my analysis. However, I do have a plausible explanation that I
consider when I apply the projection techniques discussed
above.
There are numerous target projection techniques including:






Measured moves
Fibonacci extensions
Channel projections
Andrew’s Pitchfork
Point and figure projections
Chart pattern targets
While they seem diverse, it is in fact not a challenge to describe
them in general terms. Basically, they focus on a price
formation (wave, thrust, consolidation, trend line or pattern)
and measure its magnitude (in terms of price). Then, they
project a target from the same price formation by the measured
magnitude. This pretty much sums up all target projection
methods.
I believe that in each case, the price formation used for target
projection is one that indicates the participation of the big
market players or what some traders call the institutions. The
general consensus among small retail traders is that the big
players are smarter. Hence, when these smart monies flow into
the market, they are probably expecting a significant market
move. And it is reasonable to believe that the price impact of
their entry (i.e. the price formation used for target projection)
reflects their expectations of the extent of the subsequent move
(i.e. the projected target).
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The above explanation is also consistent with the observation
that price thrusts at the beginning of a trend and out of
congested price action work better. To kick start a trend or to
push the market out of a prolonged congestion definitely require
the participation of the big players.
This is why I am selective about the price formations I use to
project targets. I stick to clear and obvious price thrusts for
target projections.
Finally, despite the numerous options for target projection, you
should focus on using one or two of them for consistent trading.
Using too many target projection techniques is like using too
many trading indicators. Despite being valuable individually,
trying to use a dozen of them adds more confusion than
efficacy. It is not worth it, especially when no projection
technique works 100% of the time.
3.2.3 - Price Channels
Price channels are powerful tools for profit taking. In addition,
they offer a gauge of how realistic your targets are.
Drawing a Price Channel
To draw a price channel, you need to know how to draw a trend
line. (Not sure? Refer back to Volume II.)
To get a bull channel, follow these steps.
1. Start with a bull trend line.
2. The bull trend line has two pivot points. Find the highest
price point in between the two pivot points.6 That’s the
origin of your channel trend line.
If there are two more equal highest price points (for e.g. double top), use the point
that will produce a narrower channel.
6
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3. From that origin, draw a line that is parallel to the bull
trend line.
To get a bear channel, follow these steps.
1. Start with a bear trend line.
2. The bear trend line has two pivot points. Find the lowest
price point in between the two pivot points.7 That’s the
origin of your channel line.
3. From that origin, draw a line that is parallel to the bear
trend line.
Figure 3-8 demonstrates how to draw a bear channel. The
resulting channel trend line turned out to be an effective target
objective.
1. Bear trend line drawn
with these two pivot points
A
B
2. Lowest point
between the
two pivots;
draw a parallel
line starting
from here
C
3. Look at how the channel trend
line served as support; good idea
to cover short positions here
Figure 3-8 Drawing a bear channel
If there are two or more equal lowest price points (for e.g. double bottom), use the
point that will produce a narrower channel.
7
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Chapter 3 - Targets
For most charting software, you can draw a channel by selecting
the channel drawing tool and clicking the points A, B, C in
sequence.
1. This bear trend line was drawn with these two pivot highs.
2. In between the two pivot highs, we looked for the lowest
price point. From there, we added a line that was parallel to the
bear trend line.
3. Look at how the bear channel trend line acted as support. A
good support is a good target for short trades.
In this case, even if you think that the market would fall lower,
covering at the channel trend line would have helped you avoid
a strong adverse movement against your position. You can then
re-enter your short position later at a better price.
As trend lines get adjusted, the corresponding new channel
become effective. Figure 3-9 below shows an example using the
price action that follows Figure 3-8.
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2. This bear channel was possible
after the market fell below point C
A
B
1. The channel
from Figure 3-8
C
3. Channel trend line offered a
great exit for short trades again
Figure 3-9 Adjusting the channel to stay relevant
1. The dashed lines mark the channel from Figure 3-8.
2. After the market fell below point C, point B became a valid
high. That allowed us to draw a new steeper bear trend line.
Together with this new bear trend line, we drew a bear channel.
3. This channel trend line, like the one in the last example,
served as a great target for short trades.
Targeting with a channel means shifting your target limit order
with every new price bar. This is because the price channel
offers a moving target, one that gets more ambitious over time.
What you can see from Figure 3-8 and Figure 3-9 is a common
scenario. Right after a price channel is formed, the market
moves quickly to the channel trend line before bouncing up with
equal swiftness.
Hence, in actual trading, to use a channel trend line as your
target objective effectively, you need to anticipate the channel.
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This means drawing potential channels, even before a trend line
is confirmed. By anticipating the channel, you can place and
adjust your target limit orders in advance.
Channel Expansion
When the market is in break-out mode and you expect large
price swings, narrow or shallow channels might offer targets
that are too conservative.
In that case, it might be useful to consider an expansion of the
price channel. You can expand a channel by drawing an
additional parallel line at an equal distance away from the
channel trend line.
Figure 3-10 shows an expanded price channel.
3. 200% line
target hit
200% line
2. Equal distance
Channel trend line
or 100% line
Bull trend line
1. Bull trend line drawn
with these two pivots
Figure 3-10 Expanding a price channel
1. This bull trend line was drawn by connecting these two
pivots. It was the basis of our bull channel.
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2. The distance (in terms of price) between the trend line and
the channel trend line is the same as the distance between the
channel trend line and the 200% line.
I also call the channel trend line as the 100% line to distinguish
it from the 200% line.
3. A target set based on the 200% line turned out to be
accurate to the tick.
Once you understand how to expand the channel to the 200%
line, you can work out further expansions. (E.g. 300% lines and
400% lines)
Guidelines for Using Price Channels
Here are some useful notes for trading with price channels.
Normal targets should stay within the channel trend line (100%
line). Targets beyond the 100% line are ambitious and might be
unrealistic. This is a rule of thumb you can apply to evaluate
target options.
For instance, you have two target options for a long setup. One
is slightly below the 100% line and the other one is slightly
above it. Despite the fact that the two targets are just a small
distance apart, the market is a lot more likely to hit the target
below the 100% line, at least before any deep retracement.
For narrow and/or shallow channels, 200% lines can be
considered for setting target objectives. However, always
exercise greater caution when using target objectives beyond
the 100% line.
The earlier figures show textbook examples. You will encounter
messier situations in your trading. Channels do not always work.
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At times, the market might fall short of the 100% line or it
might go far beyond it. Like any other profit-taking method, it’s
not perfect.
Just like trend lines, the more reliable channels are those
formed at the beginning of a new trend.
Although price channels are built on the concept of trend lines, I
did not write about them in detail in Volume II where we
covered market bias and trend lines. This is because I use price
channels primarily as a profit-taking tool to set my target
orders, not as a tool to determine market bias.
But clearly, channels have more to offer.
In general, all channel trend lines are potential support and
resistance. You can interpret them in the same way you look at
other forms of support and resistance.
An example is the flipping of support into resistance and viceversa. Figure 3-11 below shows how a broken bullish 100% line
flipped from a resistance into a support.
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2. 100% line
broken here
3. The market found
support at the
broken 100% line
1. Bull channel
drawn from here
Figure 3-11 Channel trend line flipped from resistance into support
1. This bull channel had its origins many bars back.
2. This bullish trend bar broke above the 100% line resistance.
3. Thereafter, the broken 100% line clearly acted as a support
for the market.
Recall that we draw our trend lines with valid pivots. That is
because we want to stick to the most significant trend lines and
limit the number of trend lines on our charts. We want a clean
chart that we can actually analyse.
Channel trend line offers another reason for drawing trend lines
selectively. Imagine drawing every trend line you can with every
pivot you can find, together with their channel trend lines.
Figure 3-12 shows the disaster you will get with that approach.
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Figure 3-12 Many lines, little value
The point is that a few consistently drawn trend lines, with the
added utility of a channel, are sufficient for sound price action
analysis. Keep your charts simple and uncluttered.
3.2.4 - Volatility Projection
We have used the concept of market volatility (average bar
range) for adjusting stop-loss orders. Naturally, it is also
sensible to project profit targets with volatility.
Although I do not use volatility targets extensively, it is useful
when there is no suitable price formation for target projection.
Volatility-based profit targets are also more robust as they
depend on the market’s objective volatility rather than our
subjective selection of the base price formation.
Generally, the range of price bars expands as it moves in the
direction of the market bias and contracts when it retraces
against the trend. This means that when the market is rising,
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the average range of bullish bars is higher than that of bearish
bars.
Thus, in a bullish market, it is conservative to assume that that
each bullish bar is of average bar range.
Then, let us consider the average number of bars in a price
swing. Again, we would expect more bars in an impulse wave.
This means that generally, there should be more price bars in
an upswing compared to a downswing when the market bias is
bullish. According to observations across instruments and time
frames, the average number of bars in a price swing is around
three.
Hence, in a bullish market, the assumption that each upswing
has three price bars is again a conservative one.
In the case of a bullish setup, our ideal setup bar is the first bar
of an upswing. Hence, we expect the swing to last another two
bars before coming to an end.
Combining this expectation with our earlier assumption that
each bullish bar is of average bar range, the implied target is
located at two times the average bar range above our entry
price. (The average bar range is the long-term average
described in the Wide Range Bar Trail in Chapter 2.)
Relying on the same logic, in a bearish market, we can safely
assume that the average bearish bar range is the average bar
range, and the average bearish swing has three bars. Since we
expect a short setup bar to be the first bar in a downswing, the
implied target is also two times the average bar range below our
entry price.
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VOLATILITY TARGET
Aim for a profit that is two times the
average bar range
Figure 3-13 shows an example of a volatility target projection
for a long setup.
Target
3. Average bar range was
11 ticks, so we projected
a target of 22 ticks
1. Bullish Pressure Zone
2. Not ideal for
target projection
Figure 3-13 Projecting a volatility-based target
1. We were considering our target options for this long Pressure
Zone setup.
2. There was only one three-bar bullish thrust. However, it was
not an ideal thrust to use for target projection as only the last
bar in the thrust was a bull trend bar.
3. Hence, we decided to go with a volatility target. The average
bar range was 11.7 ticks. We rounded it down to 11 ticks and
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doubled it to obtain a potential reward of 22 ticks. Then, we
placed a target 22 ticks above our entry price.
As you can see, the market made its way up to our target.
However, it was nothing like the orderly and ideal swings that
we visualised in deducing the volatility target. It took three
swings and 15 price bars to reach the target, and not the one
swing and 2 price bars that we assumed.
This volatility approach is based on an orderly market with ideal
swings in the direction of the market bias and might seem
simplistic. But it is made up of conservative assumptions and
logical deductions. Hence, it does offer a reliable targeting
option when we lack other basis for targeting. Whatever it lacks
in precision, it makes up with simplicity.
Of course, you must still evaluate volatility targets like any
other target projection technique and consider them within the
context of market support and resistance. If there is significant
support/resistance standing in between the market and the
projected volatility target, the reliability of the volatility target
decreases.
3.3 - Exiting with a Reversal Signal
The three techniques discussed above help us identify potential
profit targets. Then, as we enter the trade, we place a target
limit order at the level we choose.
Adopting a passive approach, we would wait for the market to
hit our target before exiting. There is no further meddling. This
is the recommended approach for beginners. As you gain
experience in reading price action, you can consider early exits
based on reversal signals.
When we project our profit target levels, past price action is our
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basis. However, that does not mean that ongoing price action is
useless. In fact, the current market movement provides more
timely signals for exiting our positions.
Thus, the question we are looking at now is if the market
presents a reversal signal before our target is hit, do we exit?
It depends on the quality of the reversal signal. Since reversal
signals go against the market bias, most of them will fail as the
market resumes its trend. Hence, we should ignore most
reversal signals. However, if the reversal signal is especially
strong or worrying, it might warrant an immediate exit.
The possible reversal formations that could prompt an early exit
are varied and impossible to enumerate. Thus, in this section,
we will focus only on two highly effective price formations that
should prompt an early exit.
3.3.1 - Anti-climax Pattern
As we saw in Volume III, the Anti-climax pattern is very
effective at finding market tops and bottoms. When the Anticlimax pattern forms at a support or resistance area, it offers an
extremely good reason to exit our trade.
Figure 3-14 and Figure 3-15 show an example where a bullish
Anti-climax pattern gave us the last warning to grab our profits.
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2. Short Congestion Breakout Failure setup bar
1. Price broke below the
last swing low and the bull
trend line with momentum
3. Bullish Anti-climax
Figure 3-14 Short Congestion Break-out Failure trade
1. After forming several bars showing increasing upper shadows
(selling pressure), the market broke below the last swing low
and the bull trend line with firm momentum. This confirmed that
the market bias had turned bearish.
2. Following the bearish thrust, price formed a congestion
pattern. Price broke out above it and failed immediately,
presenting us with a short Congestion Break-out Failure setup.
We shorted a tick below this bar. In this case, the bullish breakout bar was not apparent. Hence, it was not surprising for the
market to try to rise once more before plummeting.
3. The second downswing after our entry was a bullish Anticlimax pattern.
Figure 3-15 shows the price action prior to Figure 3-14. It points
out why we had to exit with the bullish Anti-climax pattern, in
the event that we haven’t already.
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2. Starting point of
the last bull trend line
1. Shorted here
Tested low
Valid low
3. Bullish Anti-climax was the
second test of the valid low
Figure 3-15 Bullish Anti-climax at a major support
1. For ease of reference, this bar corresponds to the short setup
bar shown in Figure 3-14.
2. We have marked out the support levels as our potential profit
targets. The closest one was the starting point of our last bull
trend line. As the bull trend line was relatively short-lived, this
support was not significant. The next level was a tested low. The
furthest and most ambitious target was a valid low.
3. The bullish Anti-climax pattern formed as the market tested
the valid low for the second time. Given that the valid low was a
potential major support level, we should have placed our profit
target at that level. If for any reason we did not do that and
were still in the short trade, the bullish Anti-climax gave us the
last warning to exit before the market erased our profits.
Anti-climax patterns are effective when you are looking for
potential reversals that might prompt an early exit.
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3.3.2 - Merged Congestion Zone
When the market runs into a Congestion Zone, it can either
move past it swiftly, reverse, or start to congest.
Let’s say we are in a long trade and the market rises into a
Congestion Zone. If it rises above it without stalling, there is no
reason for us to exit. If it reverses, we need to look at the
quality of the reversal pattern to determine if it warrants an
early exit. Most reversal patterns are merely false signals to trap
more counter-trend traders. Hence, we should not treat every
reversal signal as a signal to exit.
The situation we are talking about here is the third scenario in
which the market starts to congest within a Congestion Zone.
The overlapping congestions will produce a merged Congestion
Zone.
A market congesting within a Congestion Zone is an ominous
sign. There isn’t clear strength busting through the Congestion
Zone, and there are no reversal signs for us to examine. With
our greatest effort, all we can decipher is the uncertainty
brought about by this new Merged Congestion Zone.
Facing such development, we should exit at the market and wait
for clearer signs to emerge.
Figure 3-16 shows an example of a merged Congestion Zone
within the context of a short trade.
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1. Short Congestion Zone setup
2. Valid low was
a good target
3. Congestion Zone was
also a possible target
4. New Congestion Zones were a
clear signal to cover our shorts
Figure 3-16 Congestion to the power of three
1. We took a short Congestion Zone setup that occurred after
the bull trend line was broken.
2. This valid low was a good profit target.
3. The Congestion Zone below was also a reliable target option.
4. As the market descended into the Congestion Zone, it formed
two more Congestion patterns (drawn with solid lines). This
phenomenon of overlapping congestion was a clear signal that
this price zone was a key support. Traders who have not
covered their shorts should do so.
Figure 3-17 shows the subsequent price action to highlight the
power of merged Congestion Zones.
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1. The same short
Congestion Zone setup
3. See how the
market rose
2. Congestion within congestion
Figure 3-17 Congestion Zone became the low of a new bull trend
1. This was the short Congestion Zone setup shown in Figure
3-16.
2. This was the point where the market was forming new
Congestion Zones within a prior Zone.
3. The resulting merged Congestion Zone turned out to be the
low of a new bull trend.
Figure 3-18 shows another example of a Merged Congestion
Zone exit.
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1. Bear trend line drawn
with this valid high
2. A bearish Deceleration setup bar with
resistance from a Congestion Zone,
trend line, and the last basic pivot
3. Congestion Zone projected
from several sessions ago
4. New Congestion Zones were a
clear signal to cover our shorts
Figure 3-18 Trapped by congestion
1. This session opened with a bullish gap from the last session.
However, the market fell and soon formed a valid high. Using
this valid high, we drew a bear trend line and took on a bearish
market bias.
2. This was the setup bar of a bearish Deceleration setup. This
setup was particularly impressive as it occurred with the
blessing of a Congestion Zone, bear trend line, and a basic
pivot. Moreover, the five-bar thrust did not even clear above the
last basic high.
(However, the five-bar thrust was still a reasonable concern and
a more conservative method was to wait for a delayed entry,
which came two bars later in the form of a bearish inside bar.)
3. This was a Congestion Zone projected from many sessions
ago. It was a potential target for our short trade. However, we
placed the target order more ambitiously to aim for the high of
the last session. (Below the price range shown in Figure 3-18)
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4. As the market descended, it formed three congestion
patterns (solid line boxes). We were interested in the last two
patterns as they formed within the Congestion Zone, creating a
Merged Congestion Zone. Such price action prompted an early
exit.
Figure 3-19 shows what happened after the formation of this
Merged Congestion Zone.
1. Shorted
with this bar
3. The market cleared above
the Merged Congestion Zone
2. Covered here
4. Tested Merged Congestion
Zone twice and rose sharply
Figure 3-19 Merged Congestion Zone caught the low of the session
1. This is the short setup bar in Figure 3-18 shown for
reference.
2. We covered here due to the formation of the Merged
Congestion Zone.
3. After more sideways movement, the market rose and cleared
above the Merged Congestion Zone.
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4. Both tests of the Merged Congestion Zone met strong
rejection, confirming its significance as a support area. The
market then shot up sharply.
Both Merged Congestion Zone examples above show how
Merged Congestion Zones caught the low of a new bull trend. I
expect some temptation to trade reversals with this concept.
Is it a good idea to trade reversals using Merged Congestion
Zones?
It is feasible to construct a reversal trading strategy using
Merged Congestion Zones. If not, I would not have
recommended it for profit-taking.
However, this is not the trading approach we are focusing on
here. Our method is one that simplifies the game by focusing on
one direction and wins the game by selecting only high quality
trades.
3.3.3 - Additional Notes
As you use reversal signals to guide your trade exits, bear in
mind that support/resistance areas are still the pivotal factor in
determining when to grab your profits. Reversal price
formations merely augment the support/resistance areas.
The examples above also highlighted the same as we saw a
bullish Anti-climax pattern at a support level (Figure 3-15) and
the market’s hesitation around a Congestion Zone acting as
support (Figure 3-17).
Since reversal signals are effective for profit-taking, is it
possible to do without profit targets and simply let reversal
signals show us when to take profits?
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It is possible but there are several challenges to this approach.
First of all, exiting based on reversal signals requires a high
level of discretion that only experienced traders can exercise
effectively. Regardless of the exact reversal signal, exiting at
the market when a reversal signal occurs requires not only swift
interpretation of market conditions but also extreme discipline.
The slightest hesitation on the part of the trader would cause
him or her to miss the best opportunity for exiting.
Moreover, if greed takes over, the trader might be tempted to
hold the position despite the reversal signal. These factors cause
confusion and disrupt our exit strategy. Without a clear plan for
taking profits, we will never be profitable.
The next problem is that of assessing positive expectancy. We
have mentioned this challenge before in our discussion on stoplosses. Without a fixed target order, our reward-to-risk ratio is
unknown. This would obscure our assessment of the expectancy
of the trading setup.
I am not saying that we must have a fixed profit target in order
for our trades to exhibit positive expectancy. What I mean is
that the expectancy of our trades becomes harder to assess
without a fixed target. The implication is that we become
increasingly unsure of our trading edge. Again, this might not be
a problem for experienced traders who have already verified
with their track records that their discretion does more good
than harm.
Finally, taking profits with reversal signals, like all the other
techniques, is not perfect. The market does not always offer a
clear reversal signal before turning back. A sharp reversal
without warning is possible, especially in fast-moving markets.
In such cases, we might get stopped out before we could react
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to the reversal. If we had a profit target working in the market
near a support/resistance zone, we might have exited already.
Nonetheless, exiting by observing price action instead of having
static targets is reasonable. When used correctly by skilled
traders, it has the potential to do better than static targets.
Thus, my advice is that you should practise exiting based on
reversal signals only after you have mastered the skill of
reading price action in real-time. Meanwhile, I strongly
recommend that you maintain a profit target limit order in the
market whenever you get into a trade. Having actual stop-loss
and profit target orders in the market helps to ensure a
disciplined and orderly exit.
3.4 - Targeting Examples
We will go through more trading examples to demonstrate the
analysis needed to find reliable profit targets.
Before that, let’s go through the steps.
1. Plot the three closest resistance and support areas for
bullish and bearish targets respectively. Include channels
if possible.
2. Project targets using price thrusts.
3. Look for confluence of potential targets.
In your evaluation, consider the following (listed from the most
important to the least):



Confluence (clustering) of support/resistance and
projected targets
Support/resistance
Projected targets
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Confluence is extremely important for setting profit targets. An
example of a good cluster target for a long trade is two bullish
price thrust projections clustering just below a resistance level.
You will find more examples below.
3.4.1 - FDAX 10-Minute Example
In this example, we will consider our options for setting targets
for the long Pressure Zone setup shown in Figure 3-20.
1. Original bearish
market bias
3. Bullish momentum
confirmed the bullish bias
2. Far below
the trend line
4. Bullish Pressure Zone
Figure 3-20 Long Pressure Zone setup
1. The market was exhibiting a bearish bias.
2. However, price fell too far below the bear trend line and we
became alert for any sign of reversal to a bullish bias without a
trend line break.
3. This upthrust had a strong close above the previous swing
high and managed to stay above it for three complete price
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bars. Its strong bullish momentum confirmed a bullish bias
change.
4. Hence, we considered taking this bullish Pressure Zone setup.
Concurrently, we were on the lookout for potential target levels.
Figure 3-21 shows a safe and reliable target option.
3. Two-bar thrust
projection
2. Last
extreme high
4. Another bullish
Pressure Zone
1. Long Pressure Zone setup
Figure 3-21 A conservative target at the last extreme high
1. I have marked out the long Pressure Zone setup we
discussed above for ease of reference.
2. The last swing high before price retraced down to offer this
long entry was the obvious and highly reliable profit target level.
It was the most conservative target option.
3. A two-bar bullish thrust led us into our trade. Using this
upthrust for target projection, we obtained a target that was
slightly above the last extreme high. It confirmed that a target
placed at the last swing high was reliable.
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Note that this projection was possible only after our long
Pressure Zone entry. Hence, we could not have considered it
before taking the trade. However, it gave good confirmation for
traders who decided to place their target at the last extreme
high.
4. If you missed the first Pressure Zone setup, you would be
considering a late entry. The market offered a second bullish
Pressure Zone setup. Traders considering this second setup
would have greater confidence in the target due to the
confluence of the prior swing high and a price thrust projection
level.
We also considered another target as shown in Figure 3-22.
2. Congestion Zone
3. Two-bar thrust
projection
1. Long Pressure Zone setup
Figure 3-22 An ambitious but reasonable target
1. Again, we have marked the same long Pressure Zone setup.
2. In this case, we looked beyond the last swing high for the
next resistance area. We found a Congestion Zone that formed
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earlier in the trading session. It was a potential resistance area
and served as a reasonable price target.
3. On top of that, the projection from the strongest bullish price
thrust in the session so far produced a target price that was
slightly above the Congestion Zone.
Considering the close proximity of the Congestion Zone and the
projected target, placing our target limit order a tick below the
Congestion Zone was a sound move, albeit more ambitious than
the target in Figure 3-21.
The bear trend line was also a significant overhanging
resistance. Using a trend line for targeting is not a fixed target
approach as the price level of the trend line changes with each
price bar. It is a dynamic approach that requires us to adjust
the profit target to match the trend line level.
Here, the trend line was relatively shallow and overlapped with
the Congestion Zone for several bars. Due to this confluence of
resistance, the Congestion Zone was a very reliable profit target
level.
3.4.2 - ES 10-Minute Example
Figure 3-23 shows a bullish Anti-climax setup. Let’s see how the
possible targets for this setup were found.
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Bullish Anti-climax
Figure 3-23 Bullish Anti-climax setup
To find potential profit targets, we had to look for resistance
levels from the (far) left of the chart as shown in Figure 3-24.
3. Tested pivot high
2. Basic pivot high
1. Bullish
Anti-climax
Figure 3-24 Resistance level as possible targets
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1. The last bar on the chart shows the bullish Anti-climax setup
bar.
2. The basic pivot high from four sessions ago served as a minor
resistance. Given that it matched the current high of the session
we were trading in, it was a promising target level.
3. This tested pivot high was also the start of the significant
decline that the market was then recovering from.
In order to consider projected targets together with the
resistance levels we identified, we need to zoom in again to the
current session. Figure 3-25 shows the entire session. The
resistance levels we identified in Figure 3-24 are marked out for
comparison.
Tested pivot high
2. Target projected from
a three-bar thrust
3. Target projected
from a four-bar thrust
Basic pivot high
1. Bullish
Anti-climax
Figure 3-25 Not much confluence of potential targets
1. We have the same bullish Anti-climax pattern here as a point
of reference.
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2. Using the three-bar bullish thrust just before the Anti-climax
pattern, we projected a target. This target level did not enjoy
any confluence.
3. With a four-bar thrust after our entry, we managed to project
another target. As this projection was only available after our
entry, we could not use it for setting our initial target. However,
we could consider it in our trade management, assuming we
were still in the position by then.
Considering the above, the high of the session at the point of
our trade entry was the most reliable target as it enjoyed
confirmation from a basic pivot high.
The tested pivot high was also a reasonable, albeit ambitious,
option as it represented a major resistance level. Although this
level stayed beyond the grasp of the market in this session, it
was hit a couple of sessions later.
As for the projected targets, they turned out to be the best
target option for the trade within this session. Placing our target
order in the middle of the two target projections would be
perfect. However, we should not justify the means using the
ends, at least not with a single trade outcome.
When we were considering our target options, the projected
targets did not enjoy any sort of confluence. They did not
appear as reliable targets. Hence, despite the outcome, we
should stand by our analysis. (Unless, across a large sample of
trades, you find out that projected targets without confluence
served as better targets consistently. From my experience,
confluence is always more reliable.)
Wait a minute. After discussing so much, which one is the best
target level?
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There is no best target level. There are only acceptable ones.
And what is acceptable depends on our holistic assessment of
the market bias, the setup, and the target. A target that
together with the market bias and the setup offers positive
expectancy is one that is acceptable. This is something we will
work on in Chapter 5.
3.4.3 - 6J 10-Minute Example
You should have gathered by now that looking for targets
requires looking back (to the left of the chart). Figure 3-26
shows another example. Don’t worry about the details. We will
zoom in later. For now, we just need to see the larger picture.
3. Points of interest are circled
1. Long setup
2. Look for potential
resistance by looking left
Figure 3-26 Looking for resistance on the left
1. The long setup bar in this case is the right-most bar on this
chart. Figure 3-26 shows exactly what we would see before
taking the setup.
2. In our quest for possible targets, we looked left, searching for
potential resistance.
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3. The significant pivot highs and congestion patterns are
circled. From these points, we projected the resistance lines
across the chart.
Now, let’s consider our options more closely in Figure 3-27.
4. Four major
resistance
areas above
3. Target projected
with a six-bar thrust
2. Confluence of Congestion Zone,
resistance level, and last extreme high
1. Long Pressure
Zone setup bar
Figure 3-27 Deciding on a target
1. The long setup we were interested in was a bullish Pressure
Zone.
2. The dotted lines wrap around a Congestion Zone. The solid
line below represents a major resistance level. Both levels were
clustered just above the last extreme high of the market before
it started to move sideways. This triple confluence made this
potential profit target extremely attractive.
3. This target was projected from a solid six-bar upthrust.
4. Above the projected target, there were four major resistance
levels projected from past pivot highs, forming a thick zone of
overhanging resistance. The market would find it difficult to
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push through this level, but would also be attracted to it.
The triple confluence mentioned in Point 2 offered the most
conservative and highest probability target. The projected target
in Point 3 did not enjoy confluence, but it was just below the
very significant resistance zone. Hence, it offered a good target
objective if you expected the market to do more than just
testing the last extreme high.
In other words, if you expected the bullishness to resume and
push the market higher, the projected target was a sound
choice as aiming above the four resistance levels would be too
risky.
Let’s see what happened with this setup.
4. Price reversed at the
lowest resistance level
3. Projected target hit
2. Price pushed through the
Congestion Zone with ease
1. Long Pressure
Zone setup bar
Figure 3-28 Interactions between price and resistance
1. We have marked out the same long Pressure Zone setup bar.
2. Price pushed through the Congestion Zone, which was also
our most reliable target, with ease. It was a signal that the
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market was likely to rise undeterred until the next significant
resistance.
3. Hence, it was not surprising that the projected target was hit
within the next three bars.
4. Our anticipation of resistance beyond the projected target
came true as price reversed right below the lowest of the four
resistance levels.
In the retracement, the market fell just a little short of the
Congestion Zone before resuming the trend. It then tried to
push against the resistance level again.
3.4.4 - CL 3-Minute Example
If you have decided to manage your trades actively, this
example is for you. Here, I’ll demonstrate how to adjust targets
using the price action after our trade entry.
This is a more complex example. As I’ve said, active trade
management does complicate things.
In this example, we are looking for possible targets for the
Congestion Break-out Failure setup shown in Figure 3-29 below.
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Long Congestion
Break-out Failure
setup bar
Figure 3-29 Long Congestion Break-out Failure setup bar
In the recent past, there were three significant resistance levels
as shown in Figure 3-30 below. There was also a projected
target with the six-bar bull thrust.
4. Congestion Zone
5. Thrustprojected target
3. Valid high
2. Last extreme high
in this upwards trend
1. Long Congestion
Breakout Failure
setup bar
Figure 3-30 Nearby resistances as potential targets
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1. The long setup bar we were considering in this example.
2. The last extreme high was the most conservative target.
3. This valid high from the last session was a more ambitious
one.
4. This Congestion Zone could be a price magnet if the market
decides to test the price range of the last session.
5. This target was projected from the most powerful bullish
thrust of the session. This would have been a good initial target.
3. This valid high, being within the
channel seemed like a reasonable target
2. This bar confirmed a
valid low and we drew
the bull channel
1. Long setup bar
Figure 3-31 Evaluating targets with the new channel
1. We went long here.
2. This bar made a new high and confirmed a valid low for us.
With that valid low, we drew a bull channel.
3. After adding the bull channel to our chart, it was clear that
the Congestion Zone target was beyond the channel. The valid
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high from the last session fell within the channel. Hence, the
latter was a more reasonable target.
For traders who placed their target orders below that valid high,
they had a chance to shift their target upwards to the valid high
as part of their position management.
A great deal took place in the price action that followed. Let’s
take a closer look in Figure 3-32 below. This chart zooms into
the price action after our entry.
2. New thrustprojected target
1. Thrust-projected
target hit
Our setup bar
3. As the market broke the bull
trend line before resuming, the old
channel was no longer in play; the
new narrower channel took over
Figure 3-32 Powerful confluence of channel and thrust targets
1. This bar hit the thrust-projected target mentioned in Point 5
of Figure 3-30.
2. The market formed a new bullish thrust on its way up to hit
the target. Based on this new two-bar thrust, you could set a
more ambitious target here.
3. Price broke the bull trend line before resuming, prompting us
to draw a new channel (with thicker lines).
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Look at the last bar in Figure 3-32. It hit three targets at once:
1. The valid high mentioned in Point 3 of Figure 3-30.
2. The new thrust-projected target mentioned in Point 2 of
Figure 3-32.
3. The channel trend line of the new channel mentioned in
Point 3 of Figure 3-32.
This confluence of three targets was a solid reason to take profit
and close out any long positions.
Figure 3-33 shows what happened after the achievement of the
triple confluence target.
1. The bar that hit the
triple confluence target
2. The market
went into a deep
retracement
right after
Our setup bar
3. The market
resumed its bullish
path towards the
end of the session
Figure 3-33 Not perfect, but useful
1. This bar hit the triple confluence target.
2. The market fell right after the target area was hit. It was not
a shallow retracement, as it descended with good momentum.
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3. Towards the end of the session, the market resumed its
bullish path and pushed to a new high.
So, did the triple confluence target offer a good exit for our long
setup?
Looking at it ex-ante, it was definitely a good place to take
profit. Three projected resistance in close proximity is not
something you find frequently. When it shows up, it pays to
take heed.
Considering it ex-post, it showed uncanny accuracy in
pinpointing the top of a deep retracement. It reduced our time
in the market as prices went against us.
Although, of course, we can always point to the fact that the
market eventually rose higher, and our initial stop-loss (below
our setup bar) was never hit despite the deep retracement. With
that in mind, we can complain that the target was not good and
that we should have held our trade until the end of the session
for a greater gain.
But that’s not a healthy perspective for a trader, for two
reasons.
First, perfection is not what we are after. Chasing after the
perfect exit will not make you happy and will not make you
money.
Focus on finding reliable targets based on information you have
before and during the trade, not on regretting and complaining
after the trade has ended.
Second, a target must be judged together with your stop-loss
and entry.
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If you do not trail your stop-loss and give it sufficient room for
that deep retracement, it might be fine to hold on to your
position and choose not exit at the triple confluence target.
But it was certainly a good idea to exit if you’ve already trailed
your stop-loss to the last swing low.
By doing so, you were giving the trade less room to breathe.
This means that you should not be targeting ambitiously either.
For a market to hit an ambitious target, it requires more
breathing space. If you are not giving it sufficient space, then
you should use a more conservative target.
In this case, if you did not exit with the triple confluence target,
your trailed stop-loss at the last swing low would have been
stopped out during the deep retracement downwards.
3.5 - The Wrong Way to Place Targets
There are often several possible profit targets for each trade.
The closest one always has the highest probability of being
achieved. The further the profit target, the harder it is for the
market to reach it. This is because the market has to work
through more support or resistance areas and cover a larger
distance to reach targets that are far away.
However, many traders disregard this simple relationship and
choose to place their limit orders at the furthest profit target.
For day traders, a common reason for this irrational behaviour is
the desire to make up for losses incurred earlier in the session.
In fact, many day traders are so obsessed with not having a
losing session that they place their profit targets with the
intention of earning the amount they lost earlier.
For instance, a day trader who has already lost 20 ticks earlier
in the session would then place a profit target 20 ticks away. If
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his target is hit, he would not have to end the session feeling
like a loser. That is a dumb way to place a profit target.
Do not place your profit target orders further simply because
you want to make more money or wish to make up for earlier
losses. The market does not care if you want to make more
money. When you care more about something more than the
market does, you will lose.
3.6 - Conclusion
Finding realistic targets is critical to the success of a trade.
Placing unrealistic targets is very effective at ruining otherwise
good solid trade entries. Use the techniques in this chapter to
find realistic targets.
In summary, observe support/resistance and target projections
to find potential targets. Then, place a limit order at the target
level as you enter the trade.
This is especially important for day traders. As you gain more
experience and confidence interpreting price action while you
are financially committed, you might consider exiting with a
reversal signal.
Regardless of our target analysis, due to the nature of the
market, the nearest target will always present the highest
probability of being hit by the market but offer the lowest
amount of reward. The furthest target will always be hardest to
hit but offer the greatest potential reward. This is a trade-off
relationship that we must accept.
However, the trade-off relationship is not linear. The best target
is not the one with the highest probability or the one that offers
the largest amount of reward. It is the one that offers the
highest expectancy. Again, we are talking about the kinks to the
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right side of the trade-off graph between probability and
reward-to-risk ratio mentioned in our introduction. (Figure 1-4)
Having a good target is as important as having a good stop-loss.
If we enter the market without knowing when to exit, we have
no edge. You need not know exactly what price to exit at.
However, at the very least, you must know what conditions
would trigger an exit. Otherwise, it only means that you have no
way to take your profits. In that case, you will not be profitable.
It is like letting your winning lottery ticket expire because you
do not know how to claim your prize.
PROFIT TARGETS

Place a working profit target order in
the market

Observe support/resistance constantly
to look for potential targets

Watch out for confluence to find
reliable targets
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We have discussed about our stop-loss and derived our trade
risk. We have also talked about our profit targets and derived
our potential reward. Combining them will give us our rewardto-risk ratio. Now, there is only one ingredient missing from our
expectancy formula, and that is the probability of winning.
Let’s work on it now.
As discretionary traders, there is at least a part of our trading
edge that cannot be quantified or encoded mechanically.
Essentially, the trading instinct which we believe to be the
source of our trading edge seems unquantifiable.
However, we must understand that, ultimately and statistically,
our trades must exhibit positive expectancy. And to assess if a
trading opportunity offers positive expectancy, we need these
three numbers: reward, risk, and probability of winning.
With our stop-loss and target, we can easily calculate our risk
and reward. The problem lies with the winning probability. How
do we quantify that?
In this chapter, we seek to reconcile our trading instinct with the
mathematics of positive expectancy. We aim to keep things as
simple and intuitive as possible.
Recall the definition of probability of winning a trade. It is the
probability of the market reaching our target before hitting our
stop-loss.
When we are presented with a trading setup, consider its
implied stop-loss point. Then, size up the possible targets and
choose a reliable option. At last, ask yourself if it is likely that
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the market will hit the chosen target before hitting the implied
stop-loss?
If the answer is “unlikely”, forget about the trade.
If the answer is “likely”, we can then contemplate the possibility
of entering the market.
Let’s take a closer look at our answer, at the word “likely”.
When we say “likely”, what do we really mean? Can we attempt
to quantify the probability implied by “likely”?
Think of any question with the word “likely”. For instance, are
you likely to go out tonight?
Usually, this is not a question we can or are required to answer
with mathematical certainty. However, for the sake of this
exercise, let’s assume that you know you have a 90% chance of
going out tonight. In that case, you would certainly answer that
you are likely to go out tonight.
How about when you know there is an 80% chance that you will
go out? Still translates to likely.
How about 51%? If you are compelled to answer, you would
probably still agree that it is likely that you will go out tonight.
But what if there is only a 49% chance that you will go out
tonight? Would you still answer that it is “likely” that you will go
out? Probably not.
Our minds are programmed to think of 50% as a universal
threshold. Hence, I am arguing that when we conclude that
something is likely to happen, our mind in fact perceives at least
a 50% probability of that thing happening.
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It follows that when we decide that the market is more likely to
reach our target before hitting our stop-loss, the implied
winning probability is at least 50%. Of course, it could be 60%,
70%, or 90%.
However, we are traders, and we want to continue being
traders. Thus, we should be conservative and assume that our
winning probability is 50%. If your “likely to win” trades implies
a higher probability, your track record will let you know
eventually. For starters, let’s work with 50%.
When we think that it is likely for a trade to succeed, the implied
winning probability is at least 50%. However, there is a wellestablished cognitive bias that we should take into account. It is
the overconfidence bias. This bias causes us to overestimate our
abilities. This means that when we think that a trade is likely to
succeed, the lower-bound of the implied winning probability is in
fact lower than 50%.
To account for this bias, I propose that we reduce our working
figure for the implied winning probability to 40%. This figure is
partly based on pure gut feel, and partly based on my own
observation which typically shows a winning probability of
between 40% and 50% for a large sample.
Hence, the meaning of likely is 40%. This is the winning
probability that we will use in our positive expectancy
calculation.
4.1 - How to Assess the Probability of
Winning
Consider the following:


Certainty of the current market bias
Reliability of potential stop-loss level
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
Reliability of potential profit target level
Then, ask yourself this:
Is it likely that the market will reach your profit target before
hitting your stop-loss?
To answer this question, your mind goes through some
inexplicable process to sum up the three factors above. Then,
you will answer either yes or no.
If the answer is yes, it is likely that the market will reach your
target before your stop-loss, assume that the probability of
winning is 40%.
If the answer is no, assume that the probability of winning is
0%.
40%
The implied winning probability of a
trade that is likely to succeed
You might be disappointed to find out that you only have 40%
chance of winning each time you enter the market. In your
mind, you think that there must be a way to win 90% of the
time, or at least 80%.
I have three responses to this 80% to 90% winning probability
that many traders desire.
The first is that ultimately, the winning probability is not as
important as the resultant expectancy.
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You can take trades with 90% probability of winning. If those
trades have negative expectancies, you will still lose in the long
run.
You can take trades with 10% winning probability. But if those
trades have positive expectancies, you will still be profitable
over the long run. High probability trades are overrated. Taking
positive expectancy trades is the key to success.
The second response is that a higher than 40% probability of
winning is definitely possible if you select your trades very
carefully. In deducing the winning probability of 40%, we’ve
assumed the worst case scenario by taking the least implied
probability of the word “likely” and adjusting it lower to account
for the overconfidence bias. This assumption helps us to trade
conservatively until we figure out our trading edge.
A probability figure of 40% may well be an underestimation of
your winning probability. However, it is better to let your track
record show you that you are capable of finding higher
probability trades than to overestimate your own trading skills.
If your trading records reveal that your winning trades make up
a higher percentage of the trades you take, then by all means
start using a higher probability figure. You might also realise
that for certain types of setups, your winning probability is
consistently higher (or lower). In those cases, you can also
adjust the probability figure accordingly.
When it comes to estimating our winning probability, we are
almost certainly wrong, if wrong means inexact. Thus, it is
better to be wrong with an underestimation than to be wrong
with an overestimation.
If we underestimate our winning probability, we will look for
higher reward-to-risk ratios in our setups. Then, our expectancy
will be higher than expected. If we overestimate our winning
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probability, we will settle for lower reward-to-risk ratios in our
setups. Then, our expectancy will be lower than expected. It
might even become negative.
The drawback of underestimating our winning probability is that
we will end up taking fewer trades. This is because a lower
winning probability requires a higher reward-to-risk ratio to
achieve positive expectancy, and setups with high reward-torisk ratio occur infrequently. Trading less is not fatal as it is
surely more important to ensure our profitability than that of
our broker.
Last but not least, although a higher than 40% winning
probability is possible, I seriously doubt that a 90% win rate
strategy with positive expectancy exists, with the exception of
clear arbitraging opportunities.
A 90% win rate strategy is definitely possible, but it will not be
profitable in the long run. To get there, just aim for a 1-tick
profit with a 1000-tick stop-loss. DO NOT DO IT.
For this, the efficient market hypothesis offers the best
explanation. The financial markets are certainly not completely
efficient. However, they are largely efficient. Hence, it is only
logical that money-making opportunities are infrequent and
fleeting. A winning strategy with 90% win rate remains the stuff
of daydreams.
4.2 - Conclusion
In this chapter, we arrive at two simple conclusions.
The first is that when we think that the market is likely to hit
our profit target before hitting our stop-loss, we should assume
a winning probability of 40%.
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The second conclusion is that high probability is in fact not high
at all. It refers to 40%. This is why we must be very careful with
our selection of trades.
Now, armed with a probability figure, we have all we need to
pursue positive expectancy opportunities in the market.
MEANING OF LIKELY

Start with a conservative winning
probability of 40%

Adjust it higher if your track record
justifies a higher probability

Understand that positive expectancy
is more important than win rate
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Expectancy
Now that we have gathered all the pieces of the positive
expectancy puzzle, we can finally start trading.
Let’s begin with assessing the expectancy of a simple example
(Figure 5-1), before moving towards a general formulation of
our trading process.
1. Bearish Deceleration
2. Anxiety Zone setup
bar (Risk of 2.5 points)
Figure 5-1 Anxiety Zone entry and trade risk
1. In this ES 10-minute chart, a bearish Deceleration formed in
a rising market. The first two bearish bars that followed the
pattern were not triggered.
2. The third setup bar was triggered and set up an Anxiety
Zone. This bullish reversal bar was the long Anxiety Zone setup
bar. It had a bar range of 2 points. Given that we planned to
enter a tick (0.25 point) above it and place our stop-loss a tick
below it, our total trade risk was 2.5 points.
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Figure 5-2 shows how we obtained our potential profit target.
2. Implied profit
of 7 points
1. Measured move
target using this
bullish thrust
Figure 5-2 Projecting our target
1. There was no appropriate overhanging resistance serving as a
price magnet. Hence, we projected a measured move target
using the most apparent bullish thrust of the session.
2. We intended to place our target limit order a tick below the
projected level. That gave us a profit potential of 7 points.
Now, let us calculate the expectancy of this trade.
To recap:



Winning probability = W (40%)
Reward of a trade = R (7 points)
Risk of a trade = L (2.5 points)
Expectancy
= (W x R) – [(1 - W) x L]
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= (0.4 x 7) – [(1 – 0.4) x 2.5]
= 2.8 – 1.5
= 1.3 > 0
Since the expectancy is positive, we should take this trade.
5.1 - The Split Second
As demonstrated in the example above, trading requires us to
analyse the market on an ongoing basis. Concurrently, we are
trying to figure out the market bias, possible entries and stoploss levels, and possible target levels.
Then, the moment we find a reliable stop-loss and target level,
we quickly ask ourselves if it is likely that the market will hit the
target before hitting our stop-loss. If the answer is yes, we have
to decide in a split second if the opportunity offers positive
expectancy.
Most day traders would not enjoy the luxury of time that allows
them to compute the expectancy of the trade slowly like what
we did above. This is particularly true for traders operating in
fast-moving intraday time frames below the 5-minute time
frame. If you are trading slower time frames like 30-minute or
1-hour, you might be able to do so.
However, if the current price bar changes its form significantly
towards the last few seconds of its formation, it poses a
difficulty as well.
Hence, we need to devise a method or a tool to help us evaluate
the expectancy of a trade swiftly. We can first reduce the
challenge by recognising a simpler objective. In fact, we do not
need to know the exact expectancy of a trading opportunity. All
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we need to know is if the expectancy of the trade is positive. If
it is, we take the trade. If not, we pass.
To begin, let’s revisit the three key components: risk, reward,
and probability.
Our assessment of the potential risk and reward depends on our
ongoing analysis of the market as we look for reliable stop-loss
and target levels. Hence, they are constantly subject to change.
On the other hand, we are assuming that our winning
probability is always 40% when our minds conclude that a trade
is likely to succeed. Thus, it is easier to use this static
probability input as our starting point.
Given the winning probability of 40%, what is the minimum
reward-to-risk ratio required for a trading opportunity to offer
positive expectancy?
To recap:



Probability of Winning a Trade = W (40%)
Reward of a Trade = R
Risk of a Trade = L
Expectancy = (W x R) – [(1 - W) x L]
(W x R) – [(1 - W) x L] > 0
W x R > L x (1 - W)
R / L > (1 – W) / W
R / L > (1 – 0.4) / 0.4
R / L > 1.5
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Given a winning probability of 40%, we need a reward-to-risk
ratio above 1.5. Remembering this minimum reward-to-risk
ratio is extremely useful in that split second. It implies that as
long as the trade we think is likely to succeed offers a rewardto-risk ratio of at least 1.5, we should take the trade.
Let’s bring back the most important graph in this book. Look at
Figure 5-3.
Positive Expectancy
Negative Expectancy
Figure 5-3 We want to be on the right side of the graph
The sole objective of a trader is to find opportunities to enter
the market while staying on the right side of the graph where
the expectancy is positive. In that split second when the setup
bar is completed, we need to decide if we want to place an order
to enter the market.
Our reward is based on the target we projected on the chart
using projection techniques and by observing
support/resistance. Our risk is based on the bar range of our
setup bar on the chart. Since both our reward and risk are
implied by technical levels on the chart, the best way to assess
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the reward-to-risk ratio is by adding a simple indicator to our
charts.
5.1.1 - R2R Indicator
The Reward-to-Risk (R2R) indicator is a simple indicator that
adds great value to our trading process. It is immensely useful
for facilitating decision-making in that split second. This
indicator has only one mandatory input, and that is the
probability of winning. The default value is 40%.
However, depending on your trading skills and the specific trade
setup you are considering, you may increase or decrease the
probability. Essentially, it represents your judgement of how
probable it is that the market will hit our target level before
hitting our stop-loss point.
With the winning probability figure, the indicator is able to work
out the minimum reward-to-risk ratio required for positive
expectancy.
Our standard trading method involves buying a tick above the
setup bar and selling a tick below it. Hence, our trade risk is the
range of the setup bar plus two ticks.
However, in actual trading, our trade risk is slightly higher due
to trading commissions and slippage. We do not always get
filled at the price we want. When we get filled at a worse price
than where we placed our stop orders, the additional loss is
called slippage. On top of all these, there is always room for
human error (fat finger) that might cause us to incur additional
risk. I am referring to errors in executing the trade, like
accidentally placing the order at a wrong price, and not in
analysing the market. These are factors that will increase our
trade risk.
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To factor these additional risks into our expectancy analysis, you
can specify a buffer amount for these additional risks. (Default
is 1 tick.) Based on that input, the R2R indicator automatically
calculates the total trade risk.
With the trade risk and the minimum reward-to-risk ratio, the
R2R indicator computes the amount of profit necessary to justify
taking that trade. By adding the profit required to our entry
price, the indicator is able to mark out the price level that
corresponds to the minimum acceptable profit target.
Thus, our trading decision is simplified. If our target lies beyond
the R2R chart marker, we can proceed to take the trade. If our
target is within the chart marker, we should forgo the trade.
Figure 5-4 demonstrates how the R2R indicator simplifies our
trading process.
2. There was a 40% chance that
the market would reach this target
before hitting our stop-loss order
4. The target was above
the R2R projection
3. R2R projected
minimum target
1. Bullish setup bar
Figure 5-4 Split second decision-making with the R2R indicator
1. We considered buying a tick above this bullish reversal bar.
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2. We assessed the context for possible targets and decided that
the last extreme high of the trend was a conservative and
reliable target. Looking at the target and the setup bar, it was
likely that the market would reach the target before hitting our
stop-loss below the setup bar. Hence, we assumed that the
winning probability was 40%.
3. Taking the winning probability to be 40%, the R2R indicator
projected the minimum target price required for the trade to
offer positive expectancy.
4. As our intended target level was above the R2R projection,
we could take this trade without hesitation.
Figure 5-5 shows how the R2R indicator tells us that a
subsequent setup bar in the same chart was not acceptable.
2. There was a 40% chance that
the market would reach this target
before hitting our stop-loss order
3. R2R projected
minimum target
4. The target was below
the R2R projection
1. Bullish setup bar
Figure 5-5 R2R helps us say no to a trade
1. For this example, we were considering to buy a tick above a
setup bar that formed later.
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2. We assessed the probability of the market hitting our target
before our stop-loss. For the sake of illustration, let us assume
that again we were 40% certain.
3. This was the R2R projected minimum target price level for
positive expectancy.
4. As our intended target level was below the R2R projected
target, this trading opportunity did not offer positive
expectancy. Although this setup bar was a clear bullish trend
bar, it entailed a higher trade risk. Moreover, it was nearer our
target level and offered less profit potential. Hence, with the
same winning probability, this setup did not offer positive
expectancy.
The R2R indicator is not a magical indicator that finds you
trades that are guaranteed to win. However, it is a nifty tool
that constantly reminds us to look out for positive expectancy
and helps us assess trading opportunities quickly.
We offer our subjective input in the form of the winning
probability after sizing up the market bias, target level and stoploss point. (Default is 40%.) The R2R indicator then transforms
that subjective input into an objective criterion which is the
minimum target level for positive expectancy.
The principle of garbage in, garbage out applies here. Our
estimation of the winning probability is the key. The reliability of
the minimum target depends on the accuracy of our winning
probability. In turn, the accuracy of our winning probability
depends on how well we interpret the market bias, the setup,
and the selected target level. Given the correct probability input,
the R2R indicator will always help us verify if a trade offers
positive expectancy.
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Note that the R2R indicator is only valid for a trading method
that fulfils the following criteria.


Enters the market on break-out of a setup bar
Places a stop-loss order just below the setup bar
Our trading framework certainly fits the bill. If you have a
different entry and stop-loss placement technique, you cannot
use the R2R indicator. However, you can still use the same logic
to design a tool to simplify expectancy analysis.
Note that this indicator is not needed to trade profitably. I
deplore trading books that explain a marvellous trading strategy
before telling you that a proprietary black-box indicator is
needed, not to mention the fact that the indicator costs
thousands of dollars. This indicator adds only convenience and
serves as an active reminder of the concept of positive
expectancy.
5.2 - Complete Trading Examples
We have been going through piecemeal examples concerning
specific parts of the trading process. It was sufficient for
explaining and clarifying individual concepts like the market
bias, setups, targets, and expectancy. It is now time to put
them together.
In this section, we will go through complete examples that show
you how to evaluate trading opportunities end-to-end. My
intention is to show you how to trade in real-time and not how
to conduct post-trade analysis. Hence, the examples below are
based on my trading experience. They explain my actual
considerations during a trading session. (I trade mainly in the
CL and FDAX futures market.)
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For each trading example, we will discuss the following in detail.
1. Market bias assessment
2. Setup analysis
3. Probable target analysis
4. Expectancy evaluation
The market bias assessment always comes first. If you can
decipher the market bias, start to look for setups. If not, keep
watching the market.
If you change your market bias repeatedly within a short period,
it means that you are confused. Turn off your trading terminal,
and go for a walk. Listen to some music.
If you have a solid read of the market bias, you can move on to
searching for actual trading setups. In most cases, the setup
analysis and the search for probable targets would take place
concurrently.
Evaluating if a trading opportunity has positive expectancy is
the last step. Take the trade only if your evaluation of the
expectancy is positive.
To fully understand the following examples, you must be
familiar with the tools, techniques, and concepts explained so
far. If you are unclear, refer back to the relevant section before
proceeding.
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5.2.1 - CL 4-Minute Example (14 April 2014)
Assessing the Market Bias
4. Price trapped between two
trend lines; unclear bias
2. Strong bull thrust
warning against
taking short positions
1. Gap open below
the bear trend line
5. Bearish
momentum below
the bull trend line;
bearish turn
3. First valid low
6. These five bullish
bars did not reach
the last pivot high
Figure 5-6 Bearish bias
1. This session opened far below the bear trend line from the
last session. Hence, we started this session with a bearish
outlook.
2. However, the market rose for seven consecutive bars. Due to
the large distance between the market and the bear trend line,
we were sensitive to any bullish signs. Hence, this strong
upthrust was sufficient to deter us from considering any short
setup.
3. With this new valid low, we changed our bias to bullish.
4. However, the bear trend line was still effective, and there was
overhanging resistance from a Congestion Zone projected from
the previous session. Hence, price was trapped between the two
trend lines. It was wise to refrain from trading until the market
bias became clear.
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5. Eventually, the market broke below the bull trend line. The
second tested low showed momentum as one bar stayed
completely below the last pivot low. This was our signal to adopt
a bearish bias.
6. Shortly after, a series of five bullish bars made us slightly
unsure of the new bearish bias. However, the last two bars in
the five-bar thrust did not make new highs, and the entire
bullish thrust did not even hit the last pivot high.
In conclusion, the market bias was bearish. However, it
was not crystal clear, as with most newly established market
bias.
Analysing the Trading Setup
To highlight the price action surrounding the setup, we are
zooming into the later part of the chart.
1. Congestion Zone and bear trend line acting as resistance
2. Bearish
Pressure Zone
3. Setup bar implied
trade risk of 9 ticks
Figure 5-7 A high-quality short Pressure Zone setup
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1. The market found resistance as it rose into a Congestion
Zone and a bear trend line. It was the second rejection from this
resistance combination. The first was the one that led to the
break of the bull trend line. This double rejection provided an
excellent backdrop for any short setup.
2. A bearish Pressure Zone formed to confirm the selling
pressure at the resistance area.
3. The last bar of the Pressure Zone was a bearish bar and
served as our setup bar. Using our standard stop and entry
method, this bar (range of 7 ticks) implied a trade risk of 9
ticks.
This bearish Pressure Zone setup was of a high quality with solid
resistance above it.
We have defined our trade risk of 9 ticks.
Analysing Probable Targets
For this short trading setup, we considered nearby support
levels as possible targets.
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2. Valid low (33)
1. Tested low (27)
3. Session low (87)
Figure 5-8 Support levels as possible targets with implied profit (in ticks)
1. The target that the market was most likely to hit was this
tested low. This target implied a profit of 27 ticks.
2. A valid low below the tested low was a slightly less probable
target which if hit, would offer 33 ticks as the reward.
3. The most ambitious target was the session low. Ambitious
traders would be targeting 87 ticks in profit. Traders using this
target must have a strong conviction that the original bearish
bias (indicated by the bear trend line) would resume.
The first two support levels were relatively close to each other.
They were six ticks apart. Six-tick was small compared with the
average bar range in that trading session. Hence, we could
consider the zone between them as a highly reliable target zone
with the confluence of two support levels.
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Evaluating the Expectancy
Our market bias was bearish. However, as it was not crystal
clear, we would prefer a high-quality trading setup if we were to
go short. The bearish Pressure Zone setup resisted by both the
Congestion Zone and the bear trend line offered us just the high
quality opportunity we needed.
Overall, it was likely that the market would hit the most
conservative target at the nearest pivot low before hitting the
stop-loss implied by this high quality Pressure Zone setup.

Winning probability = 40%
The trade risk was 9 ticks. The profit target offered the potential
for earning 27 ticks. For simplicity, we are ignoring commissions
and slippage.


Potential reward = 27 ticks
Potential risk = 9 ticks
With these pieces of information, we can calculate our
expectancy for this setup.
Expectancy = (40% x 27) – (60% x 9) = 5.4 ticks
Hence, we expect to earn 5.4 ticks per trade over the long run
taking trades of this profile. Given the positive expectancy,
we should take this trade.
Figure 5-9 shows the outcome of this trade.
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Stop-loss
Shorted here
Target hit
Figure 5-9 A good and lucky trade
For this trade, we were lucky. Our target was hit, and we exited
with 27 ticks before commissions. In fact, our target level
turned out to be the best we could have hoped for.
Wait a minute. We were lucky?
Didn’t we scrutinise the market for its bias, a delicate entry, and
a likely target for this trade? Isn’t the success of this trade a
result of our trading skill and technique?
Yes, we did all that and determined that this setup had a
positive expectancy before entering the market. Thus, it was a
good trade.
However, even good trades fail. The market could still have
gone against us to hit our stop-loss order before hitting our
target limit order. If that had happened, it still does not change
the fact that it was a good trade.
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With our trading skills, we take good trades. Over the long run,
good trades will make us profitable. Hence, our job as a trader
is to take good trades.
However, for each individual good trade, it can either succeed or
fail. That depends on luck. It is completely beyond our control.
Recognise this.
Fortunately, over time, luck will even itself out. The good luck
we enjoy will cancel out the bad luck we suffer from. Hence, as
long as we focus on taking good trades, we will be consistent.
The point is that even if this trade resulted in a loss, we should
not regret taking it, because it is a good trade.
The seasoned and consistent trader feels happy the moment he
enters into a good trade. Even if the trade ends up with losses,
the perfect trader remains equally content because he took a
good trade with rigorous analysis and clear procedures.
An amateur trader feels happy only after he exits the trade with
profits. If the trade ends up with losses, the amateur feels
unhappy because he has lost money by taking the trade. This is
because the amateur does not care if a trade is good. He just
wants winning trades. That’s unrealistic.
We will return to this idea later when we discuss the Ultimate
Litmus Test.
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5.2.2 - CL 4-Minute Example (1 May 2014)
Assessing the Market Bias
2. This strong bull thrust
might be a sign that the
bias has turned bullish
1. A gap open
below the bear
trend line
6. With this new high, the
bull trend line was adjusted
to the shallower solid line
5. This bear trend line
acted as resistance for a
while before breaking
3. The first tested
low showed relatively
weak momentum
4. Valid low that allowed us to
draw the dotted bull trend line
Figure 5-10 How the market turned from bearish to bullish
1. The session opened with a gap below a bear trend line that
originated from past sessions. Despite the extreme bullishness
of the session’s first bar, we started with a bearish market bias.
2. As the first tested high of the session showed bullish
momentum, we considered if the bias had turned bullish. While
this development was sufficient to deter us from taking bearish
setups, it was premature to confirm a bullish bias. This upthrust
was also a bearish Anti-climax pattern, which we did not take
due to the bullish momentum and the lack of resistance at that
level.
3. The short Anti-climax setup showed promising follow-through
downwards. However, as it formed the first tested low of the
session, it was unable to exhibit clear momentum. Although it
managed to close below the last pivot low for two bars, it was
unable to clear below it.
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4. As the market rose, it formed the first valid low of the
session, and we drew the dotted bull trend line based on it. We
then assumed a technical bullish bias.
5. However, we did not rush in to look for bullish setups as the
bear trend line was still an effective resistance. Furthermore,
the market has risen near the bear trend line and offered little
room for potential profits. The bear trend line did not hold as a
resistance for long. Eventually, price meandered sideways and
broke it.
6. Then, the market pushed up to make a new high, giving us
the green light to adjust our bull trend line to accommodate the
recent sideways action.
Based on the adjusted bull trend line, the clearing of the bear
trend line, and the lack of bearish momentum in the session, we
changed our market bias assessment to bullish.
Analysing the Trading Setup
For clarity, Figure 5-11 shows a close-up of the price action just
after the bear trend line was broken.
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2. This bar did not
clear above the
Congestion Zone
1. Three-bar
congestion pattern
3. Confluence of support
from Congestion Zone
and bull trend line
Figure 5-11 Long Congestion Zone setup with trend line support
1. In the sideways movement that broke the bear trend line, a
three-bar congestion pattern formed. Accordingly, we projected
a Congestion Zone to the right.
2. The bar that made a new high did not clear above the
Congestion Zone. Thus, according to our Congestion Zone
trading rules, we should not use the Zone as a support level yet.
3. However, we exercised our discretion and treated the
Congestion Zone as a support level for a long setup. This was
because we were certain that the market bias has turned
bullish. In addition, the bar mentioned in Point 2 almost cleared
above the Zone. It was a borderline case. (If the low of the bar
was one tick higher, it would have cleared it.)
Hence, we considered a (modified) Congestion Zone setup as
the next price bar found support from both the Congestion Zone
and the bull trend line.
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Despite not being a perfect Congestion Zone setup, it had the
support of a newly adjusted bull trend line. Hence, it was a
reasonable setup. Taking this setup entailed a trade risk of
15 ticks.
Analysing Probable Targets
Let’s zoom out again and look at the larger picture for possible
profit targets.
4. Target projected from the bullish thrust
2. Last valid high
1. High of session
3. Most powerful thrust of the session
with consecutive bull trend bars
Figure 5-12 Last valid high coincides with a target projection
1. The high of the session was of course a candidate for profit
target. In fact, it was the most reliable one.
2. If the market managed to rise higher than that level, the next
resistance level would be the price level of the last valid high.
3. For a second opinion, we identified the strongest sustained
bullish thrust of the trading session and projected a target
based on it.
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4. The projected target was just a tick below the valid high,
offering a confluence of target levels.
The high of the session was the most conservative target.
However, the next higher profit target looked reliable as well
with the confluence of a thrust-projected target and the most
recent valid pivot high. Hence, we decided to go with the
further target which implied a reward of 46 ticks.
Evaluating the Expectancy
I was sure that the market bias had just turned bullish.
Although I took some liberties with the Congestion Zone setup,
the support provided by the bull trend line was assuring.
Furthermore, I had a reliable profit target level at the last valid
high.
Considering these factors in totality, it was likely that the
market would hit the target before hitting my stop-loss.
However, does that mean that this trade offered positive
expectancy?
Let’s put our R2R indicator to use here for a quick answer. We
used 40% as our estimate of the winning probability given our
intended stop-loss and profit target. In Figure 5-13, the
horizontal mark shows the minimum target required for positive
expectancy.
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3. Intended profit target level
2. Minimum required
target level
1. Setup bar
Figure 5-13 A simple and visual way to evaluate expectancy
1. This was the Congestion Zone setup bar we were considering.
2. This blue mark above it was drawn by the R2R indicator. This
indicator marks the minimum target level that implies positive
expectancy. If our intended target is above this mark, the trade
offers positive expectancy.
3. In this case, our intended profit target at the last valid high
was higher than the R2R mark, offering us a trading
opportunity with positive expectancy. Hence, we took the
trade.
Of course, we could also go through the expectancy calculation
like the last example and deduce that the trade was worth
taking. However, the R2R indicator has greatly simplified the
process for us.
If our planned target was at the current session high, we would
not have taken the trade. It means that with a 40% certainty
that the market would hit the nearer target before hitting our
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stop-loss, the trade would not offer positive expectancy. (Figure
5-14)
2. Minimum required
target level
3. Intended profit target level
1. Setup bar
Figure 5-14 Skipping a trade with the help of the R2R indicator
1. The setup bar remained the same.
2. Since our estimation of the winning probability and trade risk
stayed the same, the minimum required target for positive
expectancy was also unchanged.
3. However, in this case, the target level was below the
minimum required. Hence, we had to skip the trade.
If your assessment of the probability (given the more
conservative target) was much higher than 40%, this trade
might be acceptable.
Take note that we do not adjust the target in order to achieve
positive expectancy. We always plan our stop-loss and target
level before considering the winning probability. Assessing if the
trade has positive expectancy is always the final step. If we
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adjust the target to a more ambitious level at this stage, we
would need to decrease the winning probability. If not, the
expectancy calculation is no longer valid.
5.2.3 - CL 4-Minute Example (5 May 2014)
Assessing the Market Bias
1. With this valid high
from the last session, we
drew this bear trend line
4. But there was no
bullish momentum
5. The first bar of
this session gapped
up and fell rapidly
2. The bear trend line 3. Pivot lows
formed above
was broken here
the trend line
6. With this new low, we
adjusted the bear trend line
Figure 5-15 A broken trend line does not mean reversal
1. With this valid high from the last session, we drew the bear
trend line (dotted).
2. The market rose and tangled with the trend line for a while
before rising above it. Instead of concluding a change of market
bias to bullish, we should observe for confirming bullish signs.
3. Pivot lows formed above the bear trend line, suggesting
bullishness.
4. However, the tested highs did not reveal any clear bullish
momentum. None of the tested highs cleared their preceding
swing highs.
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5. That included the first bar of the current session, which
gapped up before falling down swiftly. The speed with which the
opening gap was closed issued a strong bearish signal.
Moreover, this downswing cleared the last pivot low from the
last session. With these mixed signals, it was better to wait for
more price action to unfold.
6. With this bar, we were able to confirm the high of this session
as a valid high. Hence, we adjusted the bear trend line to
accommodate it. The dotted trend line was adjusted to the
higher and shallower solid trend line. With this adjustment, we
also adopted a bearish market bias.
The first downswing of this session was peculiar and worthy of a
closer look. Remember what marks the end of a downswing? An
up bar. A bar with a higher bar high and a higher bar low. Look
at Figure 5-16 and try to find the first up bar of the session.
First bar of the session
Support from the
last swing low
First up bar
Last extreme low
Figure 5-16 A single swing, technically
The first up bar of the session arrived only after the market has
cleared below two support levels. It meant that the market took
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a single downswing to clear below two support levels. The
bearish momentum was apparent. This observation
cemented our bearish outlook.
(The 6th, 16th, 17th, 19th bars had higher bar highs. However,
they did not have higher bar lows. Hence, they were outside
bars, and not up bars. If you are unclear on how I define
outside bars, refer to Volume II Chapter 3.)
Analysing the Trading Setup
For a clear point of reference, Figure 5-17 also begins with the
first bar of the session.
First bar of
the session
2. Bearish Anti-climax rising
into a Congestion Zone
3. Setup bar
1. Congestion
Zone
Figure 5-17 Anti-climax at a Congestion Zone
1. As the market tried to clear below the pivot low from the last
session, it formed a six-bar congestion pattern which we
projected to the right as a Congestion Zone.
2. After clearing below the Congestion Zone, the market rose up
into the Zone with a bearish Anti-climax pattern. We also noted
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that the Anti-climax upswing did not clear the last swing high
despite closing above it for two bars. It implied a lack of bullish
momentum.
3. The next bar was a bearish bar which was our potential setup
bar.
Considering the bearish pattern and the resistance offered by
the Congestion Zone, it was a reliable setup. Selling a tick
below the setup bar called for a trade risk of 9 ticks.
Analysing Probable Targets
To observe the larger picture for potential profit targets, we
included the past two sessions into Figure 5-18
1. Short
setup bar
2. Current session low
4. Congestion
Zone
3. Valid low
5. Targets projected
with downthrusts
Figure 5-18 Finding confluence
1. This was our short Anti-climax setup bar.
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2. A conservative target would be the current session low. If the
market resumed its bearish move, that target would certainly be
hit.
3. A more ambitious target would be the valid low from two
sessions ago.
4. This valid low coincided with the level of a thin Congestion
Zone projected from earlier price action. The confluence of the
valid low and a Congestion Zone offered a highly reliable target.
5. In addition, we also projected several targets with the bearish
price thrusts of the session. Let’s take a closer look at these
projected targets in Figure 5-19.
1. A solid downthrust for
projecting bearish target
Short
setup bar
3. Less
ideal thrust
2. Projected target
with the first thrust
4. Second projected target
within the Congestion Zone
Figure 5-19 Projected target in the middle of the Congestion Zone
1. The first three bars of the session was a solid thrust that was
great for projecting a bearish target.
2. The projected target was a little below the Congestion Zone
we first highlighted in Figure 5-18.
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3. This two-bar downthrust was less ideal for target projection.
It contained two bearish bars of which only one was a bear
trend bar. However, we still projected a target with it for a
second opinion.
4. The projected target turned out to be right in the middle of
the Congestion Zone and was just a tick below the valid low.
The clustering of a valid low, a Congestion Zone, and a
projected target gave us no choice but to choose that price level
as our intended target. The potential reward was 34 ticks.
Practically, you should be plotting these potential target levels
on an ongoing basis, even before the formation of any trading
setups. The constant question you can pose to yourself is “If I
were to enter the market now, where can I place my target
order?” In this way, once a setup appears, you can size up the
winning probability swiftly.
Evaluating the Expectancy
The market bias was clearly bearish. The trading setup
comprises a bearish Anti-climax pattern and a Congestion Zone
acting as resistance. The target was reliable with a cluster of
three support levels. Hence, it was likely that the market would
hit the target before hitting our stop-loss. The assumption was
again that we were 40% sure.
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2. Minimum required
target level
1. Setup bar
3. Intended profit target level
Figure 5-20 Evaluating expectancy with the R2R indicator
1. This was our setup bar for the short trading opportunity we
were evaluating.
2. The R2R indicator marked out the minimum required target
level for positive expectancy, assuming a 40% winning
probability.
3. As our intended profit target level was beyond the R2R chart
marker, this setup offered positive expectancy.
Hence, we should take the trade.
However, as you can see in Figure 5-21, the market did not go
our way.
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Stop-loss
level
A firm bullish bar
hit our stop-loss
Profit target level
Figure 5-21 Stopped out!
The third bar after our short Anti-climax entry stopped us out. It
was unfortunate. However, the real question was if our analysis
was consistent and did we follow our trading rules. We did.
Hence, we should not dwell unnecessarily on this loss. Instead,
we should continue to monitor the market with the same
objective lenses so as not to miss out on subsequent trading
opportunities. In particular, we should watch out for the
possibility of a re-entry.
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Re-entry
3. Did not close above
Congestion Zone
4. Possible reentry setup bar
2. Price did not clear above
the high of the setup bar
Profit target level
1. Price cleared
below the low of
the setup bar
Figure 5-22 Examining the possibility of a re-entry
1. After our entry, the market cleared below our setup bar.
However, the bearish momentum was short-lived, and we were
soon stopped out.
2. Despite hitting our stop-loss, the price bars did not clear
above the high of our Anti-climax setup bar.
3. Furthermore, the Congestion Zone remained effective as a
resistance area.
4. This bearish reversal bar was the potential re-entry bar.
Should we re-enter?
Let’s recap the criteria for re-entering a short trade and go
through them for this instance. (Table 5-1)
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No. Criterion
1
Bearish bias must be
intact.
2
Original setup must be a
high quality setup.
3
4
5
Price must not clear below
the low of the setup bar.
Price must not clear above
the high of the setup bar.
Re-entry setup bar must
be bearish.
Evaluation
Bearish bias was intact. No
sign of bullish momentum
and no bear trend line break.
The original setup combined
both an Anti-climax and a
Congestion Zone setup.
It cleared below for one
bar.
It did not clear above.
It was a bearish reversal bar.
Table 5-1 Re-entry evaluation
Technically, this instance did not meet our criteria for re-entry
as one price bar cleared below the low of the setup bar.
However, I decided to exercise my discretion, bend the rules,
and re-enter anyway. This was because the session has not
shown any bullish momentum. Thus, I was relatively confident
that the session would be bearish.
Moreover, price cleared below the low of the setup bar for only
one bar. Recall that the rationale of Criterion 3 was to ensure
that we were not re-entering trades that had already succeeded
to a reasonable extent. In this case, despite clearing below the
setup bar for one bar, it did not go anywhere near the low of the
session, which was the most conservative target for this setup.
Hence, the trade has not succeeded.
Notwithstanding my decision to re-enter, I must assess if the
re-entry offered positive expectancy. As the re-entry setup bar
had a larger bar range, the trade risk for the re-entry was
bigger than that of the original entry.
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1. Re-entry
setup bar
2. Required
target level
3. Intended profit target level
Figure 5-23 Expectancy of the re-entry setup
1. This was the re-entry setup bar. Our stop-loss would be
placed a tick above it, requiring us to risk 14 ticks.
2. Assuming a 40% winning probability, the R2R indicator
marked out the required target. (In fact, on average, re-entries
enjoy a higher winning probability than original setups.
However, for simplicity, we maintained the probability at 40%.)
3. We kept to the same profit target, and the potential reward
was 40 ticks.
Since the profit target was below the R2R marker, the re-entry
implied positive expectancy. Thus, we re-entered the
market.
Figure 5-24 shows the entire session including the outcome of
our re-entry.
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1. Anti-climax
short setup
2. Re-entry setup
3. Target hit here
Figure 5-24 Price action after the re-entry
1. This was the original short Anti-climax setup, which we were
stopped out of.
2. This was the re-entry setup bar.
3. Our target was hit with a strong bearish bar.
Before we conclude this example, there is one more point to
make. Remember how breakeven stop-loss is a bad idea? This
re-entry trade example reiterates this point.
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1. Re-entry setup
2. This bar would
have hit a breakeven
stop-loss to the tick
Figure 5-25 Just don’t try to breakeven
1. This was our re-entry setup bar. We shorted a tick below it.
2. If we had shifted our stop-loss order to breakeven (a tick
below the low of the setup bar), this bearish outside bar would
have stopped us out.
Using a breakeven stop-loss (that has no price action basis)
would have cost us our trading commissions instead of earning
us 40 ticks.
In fact, after the formation of the bearish outside bar, we could
have trailed our stop-loss order to a tick above it. Remember
that we are not against tightening stop-losses. We are against
tightening stop-losses without an analytical basis. In this case,
the high of the bearish outside bar offered a short-term
resistance point which we could rely on to tighten our stop-loss.
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5.2.4 - CL 4-Minute Example (12 May 2014)
Assessing the Market Bias
1. Gapped above the bear trend
line from the last session;
started with a bullish bias
2. Bearish momentum might
reverse the bias but none came
3. This bar confirmed
the first valid low of
the session
4. Then, we could draw
this bull trend line
Figure 5-26 Forming the first trend line of the session
1. The previous session closed with price poking slightly above
the bear trend line. The first bar of this session gapped above
the bear trend line with momentum and confirmed a bullish
bias.
2. At this point, there was no bull trend line supporting the
market. Hence, we looked out for bearish momentum that might
change our market bias but none came. However, there was no
bullish momentum as well. Basically, all the tested pivots were
unable to clear their respective preceding pivots. The market
was moving sideways.
3. Eventually, the market drifted upwards and made a new
session high. This new high confirmed the circled swing low as a
valid low.
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4. With this valid low, we were able to draw a bull trend line
from the low of the last session. The bull trend line did not pass
through the valid low because we had to accommodate all of the
price action that occurred before the current extreme high. (If
you are not sure how to draw the trend line, you can review the
rules in Volume II Chapter 4.)
Now, let’s zoom in and look at how the market interacted with
this new bull trend line. Figure 5-27 shows the same market as
Figure 5-26 but retains only the price action of the current
session.
1. Selling pressure
2. The first trend line
break lacked momentum
3. The attempt to continue the bullish trend was
rejected by a bearish outside bar; note the fivebar downthrust and the bearish momentum
Figure 5-27 A double top that changed the market bias
1. Although this bar confirmed a valid pivot low, there was clear
selling pressure. Obviously, this new price high was not met
with enthusiasm.
2. The bull trend line was broken almost immediately after we
drew it. However, a mere trend line break was not enough to
turn our bias bearish.
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3. The market tried to exceed the session high again. The
sellers reacted with a bearish outside bar strong enough to form
a double top. That reaction resulted in a five-bar downthrust.
The last bar of the thrust cleared the previous pivot low,
showing bearish momentum. At this point, we had to switch
our market bias to bearish.
Analysing the Trading Setup
1. Congestion Zone
(dotted box)
2. Bearish
Pressure Zones
(solid boxes)
3. Short setup bar for two
bearish Pressure Zones
and a Congestion Zone
Figure 5-28 A matter of Zones
1. The nearest Congestion Zone (dotted box) above the market
was projected by a tight congestion pattern. It was formed just
before the market made a new extreme high.
2. After the five-bar downthrust, the market made two attempts
to rise. However, both attempts were met with selling pressure.
Look at the solid boxes that represent bearish Pressure Zones.
In particular, the second Pressure Zone overlapped with the
resistance provided by the Congestion Zone.
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3. With the support of two bearish Pressure Zones and a
Congestion Zone, this short setup looked extremely good.
However, I had a small concern. There was a thicker Congestion
Zone surrounding the current price action as shown in Figure
5-29.
2. Intended
short setup bar
1. Seven-bar
congestion pattern
3. The market still
seemed stuck within this
larger Congestion Zone
Figure 5-29 Could the market make it out of the Congestion Zone?
1. During the meandering earlier in the session, there was a
seven-bar congestion pattern. (The arrow points to the last bar
of the congestion pattern.) It projected a thick Congestion Zone.
2. This was the short setup bar we were considering.
3. However, looking at the more recent price action, the market
had difficulty pushing out of the thick Congestion Zone. If the
market continued to be restrained by the Zone, this short setup
might not be such a good idea.
After summing up the above aspects, I decided that this setup
was still a reliable one. I had two main reasons.
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First, it was a double bearish Pressure Zone setup that found
resistance at a Congestion Zone. It was clearly a high quality
setup.
Second, although the market had difficulty moving beyond the
thick Congestion Zone, the way it was moving has changed.
Before the break of the bull trend line, the market formed
several congestion patterns.
After the trend line break, despite finding support at the bottom
of the thick Congestion Zone, the market did not form any more
congestion patterns. This was a signal that the market has
moved from a meandering phase to one that was ready to make
more substantial price swings.
This setup implied a trade risk of 9 ticks.
Analysing Probable Targets
We kept tabs on the support levels below the current market
price as marked out in Figure 5-30.
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1. Valid low
2. Current session low
5. Target projected with
the five-bar downthrust
3. Congestion Zone
from the last session
4. Low of the last session
Figure 5-30 Profit target options
1. The only valid swing low of the current session was the
obvious conservative profit target.
2. The next lower target was the lowest price of the same
session.
3. For more ambitious targets, we had to examine the price
action of the previous session. The closer one was a Congestion
Zone from the last session.
4. The furthest option shown on this chart was the low of the
last session.
5. We also projected a bearish target with the five-bar
downthrust. It was the first real downthrust of the session and
the one that led to a change of market bias. Technically, three
out of the five bearish bars were bear trend bars. For these
reasons, this downthrust was especially suitable for target
projection.
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The only sign of clustering among these levels was the
closeness between the current session low and the target
projected with the five-bar thrust.
Hence, I decided on placing a target order just above the
thrust-projected target, aiming for a reward of 27 ticks.
Evaluating the Expectancy
Given the recent change in market bias to bearish, the multizone short setup and the reliable price thrust projection target,
it was likely for the market to hit the target before reaching the
stop-loss a tick above the setup bar. It was then time to
examine the expectancy.
In evaluating our expectancy, we assumed that we were 40%
sure again. (You may adjust this figure according to your
confidence level for each trading setup. This is after all, your
most important discretionary input in the trading process.)
1. Setup bar
2. Required target
level for positive
expectancy
3. Intended profit
target level
Figure 5-31 Target must be below the R2R marker
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1. This firm bearish bar was our short setup bar. We intended to
short a tick below it.
2. According to our R2R indicator, the target for this short trade
must be below this level in order for it to result in positive
expectancy.
3. As our intended profit target was below the R2R marker, this
trade offered positive expectancy.
Hence, we placed a sell stop order a tick below the setup bar.
The next bar triggered the order. Figure 5-32 shows how this
trade panned out.
1. Setup bar
4. Breakeven
stop hit
2. Target hit
3. Warnings to exit
Figure 5-32 Target hit swiftly
1. Our sell stop order a tick below this setup bar was triggered
by the next bar.
2. The market tumbled down to our profit target without any
significant resistance. We exited with 27 ticks of profit.
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3. Subsequently, the market went sideways and found
resistance at the low of the first bar of the session, forming a
triple bottom. These signs of resistance were warning traders to
cover their short positions if they had not already done so.
(Another warning sign was the five consecutive bearish bars
that could not push the market down to a new low.)
4. Again, look at how placing a breakeven stop-loss
indiscriminately does more harm than good. Let’s say you did
not place a profit target or you had an ambitious target order
that was not hit yet. After the impressive eight-bar bearish
thrust, you wanted to let your profits run but you also wanted to
ensure that you will definitely be a winner. Hence, you adjusted
your stop-loss order to breakeven despite the fact that the
breakeven level had no technical significance. This bar would
have hit the breakeven stop-loss order to the exact tick, before
plunging down into more than 20 ticks of profit.
Some traders support the idea of having breakeven stop-losses
because of their psychological benefits. Knowing that your worst
case scenario is breakeven and that your trade will never
become a losing one offers comfort. It reduces the fear of losing
and the trader will find it easier to let his profits run. Not to
mention that this idea involves responding irrationally to an
irrational fear, its psychological benefits often backfire.
Look at the same example in Figure 5-32. Your breakeven stoploss order was hit exactly to the tick. Not a tick more or less.
Then, the market plunged down again in your favour. You felt
that your analysis was right, and yet instead of earning 20 ticks,
you merely scratched the trade.
You thought that you deserved the profits. Why is the market
against you? You will be tempted to over-trade to get back the
profits you think you deserve. Under such situations, you will
need extreme discipline to stop yourself from revenge trading.
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On a separate note, this example also highlights another
important trading concept. Entries, stop-losses, and targets are
equally important for profitability. In Figure 5-32, the market
did not hit our original stop-loss order for the rest of the
session. That meant that our choice of the trading setup (i.e.
entry and stop-loss level) was good.
However, our choice of profit target would have made a huge
difference to the trade outcome. With the profit target we chose
by observing support levels and projected targets, we ended the
trade with 27 ticks of profit.
If we did not use a profit target order or placed our target too
far away, we might still be able to exit with around 20 ticks of
profit by observing the warning signs pointed out earlier.
If we had entered the trade without placing a realistic profit
target and ignored the warning signs, we would have held the
trade to the end of the session and exited with a 5-tick profit.
The ability to choose realistic targets and to react to warning
signals is as important as choosing the best entry point. This is
especially true for day trading.
Focus on selecting realistic targets first. Learn to react to
warning signals later.
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5.2.5 - CL 4-Minute Example (15 May 2014)
Assessing the Market Bias
2. Shallow bear
trend line from
the last session
1. First bar of the session opened
with a gap past the last swing low
3. Congestion around the
low of the last session
4. Price continued to fall,
confirming the valid swing high
Figure 5-33 Gapping into a bearish market bias
1. This session opened with a down gap past the last swing low.
It showed solid bearish momentum.
2. The down gap also confirmed a valid pivot high from the last
session. Thus, we drew the bear trend line and adopted a
bearish outlook. However, as the bear trend line was shallow
and the market was a distance below it, we remained alert to
any signs of a bullish reversal.
3. Unsurprisingly, price meandered around a support level
projected from the low of the previous session.
4. After making two tested highs, the market continued to fall
with good momentum. This fall confirmed the earlier tested high
as a valid high. Accordingly, we adjusted our trend line to catch
up with this development. The result was the steeper bear trend
line.
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The steeper trend line was broken quickly as shown in Figure
5-34. It shows the price action in the current session.
1. Steeper trend line
from Figure 5-33
4. Price did not reach
the last valid high
3. Tested high could not even
close above the last swing high
2. Four-bar upthrust broke
the trend line but did not
test the last swing high
Figure 5-34
Bias change? Or not?
1. This was the steep trend line from Figure 5-33.
2. This four-bar bullish thrust broke the bear trend line.
Remember that a mere trend line break is insufficient to change
the market bias, unless there is clear accompanying
momentum. Moreover, despite the four consecutive bullish bars,
the market did not even test the last swing high.
3. This was the first tested high after the trend line break.
However, the bars could not close above the last swing high.
4. Furthermore, despite a protracted upwards drift, the market
did not even hit the last valid swing high.
Due to a lack of bullish momentum, despite the trend line break,
our bias remained bearish.
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Analysing the Trading Setup
1. Congestion Zone
4. Second Congestion
Zone setup (Re-entry)
2. Short Congestion
Zone setup
3. Re-entry setup
bar (not triggered)
Figure 5-35 Skipping the first setup
1. The earlier price action projected a Congestion Zone that
acted as a resistance area.
2. The four-bar bullish thrust bumped into the Congestion Zone
but was unable to close within in. Although it presented a
Congestion Zone short setup, I chose to skip it and waited for a
re-entry equivalent trade due to the four consecutive bullish
bars. Bullish thrusts like this, even if they do not reverse the
market bias, seldom reverse down without whipsaws. Moreover,
the setup bar in this case had a lower shadow which implied
buying pressure.
3. The preceding bullish bar would have hit a stop-loss order
placed above the short Congestion Zone setup bar. Hence, this
was a re-entry setup bar. We placed a sell stop order a tick
below this bar. However, the next bar did not trigger the sell
stop order as it shared the same low as the re-entry setup bar.
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As the best re-entries happen swiftly, I chose to cancel the sell
stop order and observe further.
Another reason for cancelling the order was that the market did
not test the Congestion Zone again for resistance.
4. This setup bar offered another chance for re-entry as the
market had not cleared above the high of the original short
setup bar (marked in Point 2). Furthermore, it was the second
bounce from a Congestion Zone and was a short double
Congestion Zone setup. This failed second incursion into the
Congestion Zone presented an excellent opportunity to get
into a short position.
This setup bar implied a trade risk of 10 ticks.
Analysing Probable Targets
At the same time, we have been looking out for support levels
below the market. These levels were potential target levels. As
usual, we had to zoom out to the larger picture as shown in
Figure 5-36.
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1. Short
setup bar
2. Current session low
3. Merged Congestion Zone
from two sessions ago
4. Another Congestion Zone
5. Low of two sessions ago
Figure 5-36 Analysing potential support below the market
1. This was the short Congestion Zone setup bar we were
analysing.
2. The most probable target was the current session low.
3. If we looked a little further, the Merged Congestion Zone
from two sessions ago was also a great option. Merged
Congestion Zones are particularly effective as price magnets as
they are made up of overlapping congestion patterns.
4. Looking further back in the same session, we found another
Congestion Zone.
5. Then, the most ambitious target option shown in this chart
was the low of the session two days ago.
Looking at the support levels, the Merged Congestion Zone was
a significant support area and it was definitely unwise to place
our target objective below it. Thus, we considered having a
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target order between the current session low and the Merged
Congestion Zone.
Let’s look at thrust-projected targets to see if there was any
confluence with the support levels.
1. Short
setup bar
2. Downthrust used
for projecting target
3. Projected target within
the Merged Congestion Zone
Figure 5-37 Projected target within the Merged Congestion Zone
1. This was our short setup bar, marked out for reference.
2. This three-bar bearish thrust was the obvious candidate for
target projection.
3. The projected target was within the Merged Congestion Zone
we identified in Figure 5-36.
Due to this confluence, we settled on using the thrustprojected target as our objective.
Placing a target limit order a tick above the projected target
gave us a potential reward of 51 ticks. (A more conservative
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approach would be to place the target a tick above the Merged
Congestion Zone.)
Evaluating the Expectancy
Again, no trade can be taken without considering expectancy.
Assuming that we were 40% certain that the market would hit
our target before our stop-loss, we used the R2R indicator to
assess if this trade was worth taking.
1. Setup bar
2. Required target
level for positive
expectancy
3. Intended profit
target level
Figure 5-38 Expectancy analysis
1. This was our short setup bar.
2. According to the R2R indicator, we should only take the trade
if our intended target was below this price level.
3. As our intended target was below it, it was an opportunity
of positive expectancy.
In this case, if you thought that it was likely for the market to
reach only the current session low (and not the Merged
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Congestion Zone), you would still enter a short position. This is
because the R2R marker was above the current session low as
well.
This highlights an important point in the development of
discretionary trading skills. Our analyses of entries, stop-losses,
targets, and probabilities might differ. However, as long as the
final expectancy analysis says positive, it is a valid trade. There
is no one path to positive expectancy.
Figure 5-39 shows the outcome of this trade.
1. Setup bar
2. Target hit
3. Merged
Congestion Zone as
effective support
Figure 5-39 Outcome of the short Congestion Zone trade
1. We shorted a tick below this bar.
2. The target was hit just before the market went into a tight
trading range.
3. This test of the Merged Congestion Zone towards the end of
the session confirmed the effectiveness of the Zone as support.
It also offered a second chance to cover any short positions.
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5.2.6 - FDAX 3-Minute Example (8 August 2014)
Assessing the Market Bias
1. This bar made a new high and confirmed the
earlier tested lows as valid lows, but it was rejected
2. These valid lows allowed
us to draw a bull trend line
3. Despite a bearish wide
range bar, this tested low
did not produce bearish
momentum
Figure 5-40 Rejection from both sides
1. After a period of meandering, the market finally made a new
session high. This bar confirmed the valid lows (circled).
However, the fact that the break-out failed immediately (as a
bearish reversal bar) was worrying.
2. Nonetheless, we were able to add a bull trend line on the
chart with the help of the valid lows.
3. As we watched carefully to assess this new development,
price fell and tested the previous valid low and the newly drawn
trend line. This price bar ended with a long bottom tail, showing
clear rejection from this support cluster.
The last bar in Figure 5-40 brought the session to a new price
high. It led us to adjust the trend line as shown in Figure 5-41
below.
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2. This five-bar bullish thrust
showed great momentum
1. This bar made a new high and we
adjusted the trend line (from black to blue)
Figure 5-41 A clear bullish market that might be overextended
1. This bar corresponds to the last bar in Figure 5-40. It showed
that the bulls have won the earlier struggle. With this new high,
we adjusted the trend line to contain all prior price action,
resulting in the shallower blue trend line.
2. The break-out upwards enjoyed strong follow-though. The
market carried on and produced a five-bar bullish thrust that
showed powerful momentum.
Both the market structure and momentum supported a
bullish market bias.
Our only concern was that the bullish strength might have
climaxed and might not continue. However, as always, unless
there are bearish signs, we prefer not to call a top. Thus, we
continued to look for bullish setups, but with caution.
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Analysing the Trading Setup
To look for trading setups, we zoomed into the price action after
the five-bar bullish thrust. (Figure 5-42)
2. Bearish Pressure Zone as the
basis for a long Anxiety Zone setup
3. Instead of falling,
the market formed a
bullish Pressure Zone
1. A successful long
Trend Bar Failure setup
Figure 5-42 Finding trapped traders
1. After the five-bar bull thrust, there were two bear trend bars.
The second bear trend bar led to a long Trend Bar Failure setup.
We skipped it as there were no other bullish signs, and we were
concerned that the market might be overextended. However,
this setup was a success and helped to cement our bullish bias.
2. As the market tried to rise higher, a bearish Pressure Zone
formed. This bearish Pressure Zone must have looked very
attractive to counter-trend traders because it came right after a
seemingly exhaustive five-bar bull thrust. Our market bias was
bullish, so we observed it for its potential as a long Anxiety Zone
setup.
3. Indeed, despite being triggered by the next bar, the bearish
Pressure Zone had poor follow-through. It presented us with a
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clear bullish Anxiety Zone. Furthermore, the three bars that
followed the bearish Pressure Zone formed a bullish Pressure
Zone. It boded bad news for the traders who shorted with the
bearish Pressure Zone.
Another notable feature of this pullback was the lack of
congestion patterns. With a bearish Pressure Zone and a bullish
Pressure Zone in such close proximity, congestion patterns were
expected but none formed. This was a sign that the Pressure
Zones represented real interest and were not just by-products
of a congested area.
With a long Anxiety Zone setup and a bullish Pressure
Zone, we have found a high-quality trading opportunity.
Analysing Probable Targets
We took a step back to study the market landscape in order to
find potential targets.
2. Congestion Zone
from the previous
session
1. Target projected from
the five-bar bull thrust
3. Target projected from
the three-bar thrust
Figure 5-43 Three options for targeting
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1. This target was projected from the five-bar bull thrust.
2. This Congestion Zone projected a potential resistance area
that we could use as a target.
3. This target was projected from a more recent three-bar price
thrust.
Both targets projected from bullish price thrusts were standing
alone, without confluence with other resistance levels.
Moreover, the pivot highs around the Congestion Zone were
basic pivots and not tested/valid pivots.
Given that the market has already breached above the low of
yesterday’s session, it was likely that price will continue to drift
up to test the nearest resistance within the price range of
yesterday’s session. Hence, the Congestion Zone appeared
to be a good target option.
Evaluating the Expectancy
3. Intended profit
target level
2. Required target level
for positive expectancy
1. Setup bar
Figure 5-44 Expectancy analysis
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1. Strictly speaking, the setup bar for the long Anxiety Zone
setup was the preceding bar (second last bar on Figure 5-44).
However, that bar did not have the support of the bullish
Pressure Zone. The next bar would have completed a bullish
Pressure Zone, offering us the confirmation that this setup was
of high quality.
2. With a high quality setup and a reliable target, we assumed
that there was a 40% chance that the market would hit the
Congestion Zone before falling below the bullish Pressure Zone.
Plugging 40% into the R2R indicator, it indicated the minimum
target level required for a sensible trade.
3. Our target based on the Congestion Zone was higher than the
R2R target marker. Hence, this trade offered positive
expectancy.
Let’s take a look at how this trade panned out.
3. Target hit
1. Setup bar
2. The market made
a strong downthrust
Figure 5-45 A great target (somewhat lucky)
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1. The setup bar is marked for reference. We bought a tick
above it.
2. The first pullback after our entry was a solid bearish thrust. If
we had decided to place an ambitious target, it would have
promoted us to rethink. (Recall that none of our target options
were particularly impressive.)
Conservative traders would have adjusted their targets to the
last swing high before this downthrust. (Slightly below the
Congestion Zone.)
3. The target at the Congestion Zone turned out great. The
Congestion Zone served as an excellent resistance. The market
could not even close above the Congestion Zone before
suffering a deep pullback.
Whenever we enjoy (almost) perfect outcomes like this, we
must remind ourselves that we are lucky. Exact precision in
trading is a myth. When we get it, we are simply lucky and luck
will even out itself. This will keep our expectations in check and
prevent us from becoming overconfident.
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5.2.7 - FDAX 3-Minute Example (31 July 2014)
Assessing the Market Bias
1. Bear trend line from the last session
2. First bar of the
current session
3. First swing of the
day continued the
bearish momentum
Figure 5-46 Healthy bear trend
1. A bear trend line extended from the previous session lent
structure to the falling market.
2. The first bar of the current session was a strong bearish bar
that closed below the last swing low of the previous session.
3. The second bar of the current session continued the bearish
momentum and cleared below the last swing low. The bearish
momentum was undeniable right from the beginning of the
session.
Given the bear trend line and the bearish momentum, our
market bias was clearly pointing down.
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Furthermore, the market was not too far below the bear trend
line which was a sign of a healthy bearish market. If the market
was too far below, sharp reversals are more likely.
Analysing the Trading Setup
Figure 5-47 zooms into the recent price action. It also shows the
next two bars of the session that we are examining.
3. Trend Bar Failure
2. Trend bar
1. Bullish Pressure Zone
Figure 5-47 Bullish reprisal
1. These three bars formed a bullish Pressure Zone. As our
market bias was bearish, our interest in this Pressure Zone was
limited to its potential failure and creation of an Anxiety Zone.
2. The last bar (setup bar) of the Pressure Zone was also a
bullish trend bar. It was a sign that at least some bullish traders
have entered against the downwards trend.
3. However, although the following bar was bullish, it was not a
trend bar. Hence, it presented a short Trend Bar Failure setup.
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To trade this setup, we would place a sell stop order a tick
below this bar.
But was this Trend Bar Failure a high quality setup?
Strictly speaking, it was not as it did not enjoy confluence from
other setups. However, we were anticipating the formation of a
short Anxiety Zone setup at the same time. More importantly,
the bearish market bias was clear.
Hence, it was reasonable to consider this short Trend Bar
Failure setup.
Let’s say we wanted to be conservative and held back our entry.
The next bar would have given us the confirmation we needed.
Figure 5-48 shows the next bar which triggered the short Trend
Bar Failure setup.
2. Short Anxiety
Zone setup bar
1. Bearish Anxiety Zone
Figure 5-48 A higher probability late entry with the Anxiety Zone
1. We constructed this Anxiety Zone based on the long Pressure
Zone Setup bar.
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2. This strong bear trend bar triggered the sell stop order of the
bearish Trend Bar Failure pattern. It was also the setup bar of
the short Anxiety Zone setup. If we did not enter a short
position with the Trend Bar Failure earlier, this bar gave us a
second chance to enter. We could place a sell stop order below
it.
This example offers excellent opportunity to explain the tradeoff between winning probability and reward-to-risk ratio. Both
the short Trend Bar Failure and the Anxiety Zone setups were
reasonable entries. The later entry (Anxiety Zone) had a higher
winning probability. However, it suffered in terms of its rewardto-risk ratio. Let’s understand why.
The Trend Bar Failure setup stood alone with no confluence from
other price action formations. Hence, we were less certain of its
reliability.
The Anxiety Zone setup presented itself a bar after the bearish
Trend Bar Failure. It enjoyed confirmation from the decent
follow-through of the bearish Trend Bar Failure setup. Hence,
this setup was more reliable.
However, it offered a worse (lower) entry price than the Trend
Bar Failure setup. Being a wide range bar, it entailed a larger
trade risk as well. Ceteris paribus, these factors led to a
deterioration of the reward-to-risk ratio. This was the price we
had to pay for the increased reliability of the later setup.
So which setup was the better one? The Trend Bar Failure or the
Anxiety Zone?
There is no definitive answer. It depends on your preference
and your assessment of the market.
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If you like high probability trades, you should wait. If you like
low risk entries, you should enter early. You cannot have both.
If you are extremely certain that the bearish market would
continue, feel free to enter early. If you need that extra push to
be certain, wait and see.
Both entries are valid as long as they offer positive expectancy.
This is an issue we will discuss again soon.
Analysing Probable Targets
In an existing downwards trend, there are usually several price
thrusts available for target projection. Figure 5-49 shows two of
them in this instance.
2. Target projected from
the four-bar bear thrust
1. Safest target
3. Target projected from
the two-bar bear thrust
Figure 5-49 Target analysis
1. As usual, the safest target was the last extreme low before
the current pullback.
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2. This was a target projected from a four-bar bear thrust from
the last session.
3. From the two-bar bearish thrust that started this session, we
projected another potential target.
From this chart, it seemed like none of the price targets enjoyed
confluence. However, as we looked further back for potential
support, we found a pleasant surprise as shown in Figure 5-50.
1. Current area
of analysis
2. Major support
from a swing low
3. Support was
close to the lower
projected target
Figure 5-50 Target confluence
1. We have been looking at this area.
2. This obvious swing low projected a major support level below
our intended entry.
3. The support level was only one point away from the target we
projected from the two-bar thrust. (This support line was also
pointed out in Point 3 of Figure 5-49.)
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This confluence highlighted this support level as a great target
option. Hence, we considered it as our target for this
trading setup.
Evaluating the Expectancy
Given the clear market bias and the solid target option at a
major support, it was likely for the market to hit our target
before hitting our stop-loss.
Earlier, we considered two possible entries with either the Trend
Bar Failure or the Anxiety Zone. Let’s examine their expectancy
separately, starting with the Trend Bar Failure setup in Figure
5-51.
1. Trend Bar
Failure setup bar
2. Required target level
for positive expectancy
3. Intended profit
target level
Figure 5-51 Expectancy analysis for the Trend Bar Failure setup
1. This was the setup bar for the short Trend Bar Failure setup.
2. For that setup bar, this was the required target level for
positive expectancy. Again, we were assuming a 40% winning
probability.
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3. Our chosen target was substantially lower than the required
target. Hence, this setup exhibited positive expectancy.
Now, in Figure 5-52, let’s examine the expectancy of the
Anxiety Zone setup that formed later.
1. Anxiety Zone
setup bar
2. Required target level
for positive expectancy
3. Intended
target level
Figure 5-52 Expectancy of the Anxiety Zone setup
1. This was the Anxiety Zone setup bar. We were planning to
sell a tick below it.
2. Assuming a 40% winning probability, this was the required
target for positive expectancy. As this setup bar had a wider
range, the trade risk was higher than that of the Trend Bar
Failure setup. Hence, the required reward was higher. This
explains why the required target price for this setup was further.
3. Nonetheless, our intended profit target met the criterion for
positive expectancy. Hence, this setup was acceptable as well.
An important caveat here is that, for simplicity, we used the
same winning probability (40%) for evaluating both setups.
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However, as we discussed earlier, we were more confident in
the Anxiety Zone setup. Hence, in reality, we should be using a
higher winning probability for evaluating the Anxiety Zone
setup. That would have led to a more favourable expectancy
result.
Figure 5-53 shows the outcome of the trade.
1. Trend Bar
Failure setup bar
2. Anxiety Zone
setup bar
3. Target hit
Figure 5-53 Target hit
After our target was hit, the market retraced upwards for four
bars before falling again. The market continued to make its way
much lower for the rest of the session. If we had held on to our
trade, we might have made a lot more.
However, that’s inconsequential within the context of a single
trade. We have taken a trade with positive expectancy and that
was all that mattered.
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5.2.8 - FDAX 1-Minute Example (20th November 2015)
I added this example in the second edition of this book. It
reflects the faster 1-minute time frame I have been trading
recently.
As I mentioned, I use the PATI (introduced in Volume II) to
monitor the market that I trade, and I prefer to trade as closely
to the MTTF as possible. The recent price action in the market
has lowered the MTTF in the FDAX futures market.
However, if you are new to trading, the 1-minute chart might be
too fast for you to perform your analysis correctly. Be aware of
that if you decide to move to a faster time frame.
Notwithstanding the faster time frame of this example, it
demonstrates the same price action approach.
Assessing the Market Bias
2. But it also confirmed
this valid high, allowing us
to add a bear trend line
1. This rejection from the new
low was slightly worrying
Figure 5-54 New bear trend line
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1. This push to a new low was rejected by the market. No bar
closed below the last extreme low.
2. At the same time, the push to the new low confirmed this
pivot as a valid high. With this valid high, we drew a bear trend
line and assumed a technical bearish bias.
As mentioned, the difficulty experienced by the market pushing
to a new low was worrying for those with a bearish bias.
Hence, examining the momentum here with tested pivots would
be useful. To do that, let’s zoom into the more recent sideways
action of the chart in Figure 5-55.
2. Bullish momentum as
this bar cleared above the
preceding swing high
1. Bearish momentum
confirmed by multiple
bar closes below the
last swing low
3. Bearish momentum
returned soon, confirming that
the bears were still in control
Figure 5-55 The bulls tried but failed
1. After a climatic bullish thrust (the bullish Marubozu), bearish
momentum showed themselves quickly. We could see that from
the ease with which the market fell below the last swing low.
2. This bar cleared above the last swing high and confirmed the
presence of bullish players.
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3. However, bearish momentum returned swiftly after that. This
bar cleared below the last swing low after the previous bar
punched below it with strength.
These observations, coupled with the fact that the market
continued falling throughout these price fights, confirmed
that the market bias was bearish.
Analysing the Trading Setup
Figure 5-56 zoomed into the price action after the rejection from
the low. The valid high we used to draw the bear trend line is
marked out as a visual anchor.
Valid high
3. Congestion Zone short
setup with the bear trend
line as resistance
1. Congestion Zone
projected from here
2. Three consecutive
bullish bars
Figure 5-56 Congestion Zone short setup
1. From here, we projected a Congestion Zone to the right. This
zone was a potential support area.
2. After the market tried to push to a new low, it formed three
consecutive bullish bars.
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3. This was a Congestion Zone short setup bar. With the bear
trend line providing resistance, this setup looked good.
While it was acceptable to take this setup, it was more
prudent to skip it. There were two reasons for skipping this
setup.
The first was the rejection from the new trend low which we
discussed in Point 1 of Figure 5-54. While this development
would not affect our bearish bias, it prompted us to be more
selective of our short setups.
The second was the three bullish consecutive bars noted above.
Three or more consecutive bullish bars represent sustained
buying and can be taken as a sign of bullish momentum.
So, let’s be patient and wait here another setup, possibly a reentry setup. The next selling opportunity came soon as shown in
Figure 5-57.
Valid high
2. Strong bearish bar
as Deceleration and
re-entry setup bar
1. Three consecutive bullish
bars forming a bearish
Deceleration pattern
Figure 5-57 A better re-entry setup with bearish Deceleration
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1. Shortly after the Congestion Zone short setup was triggered,
the market formed another series of three bullish bars. But in
this instance, the three bars also formed a bearish Deceleration
pattern. Furthermore, the last two bullish bars were Dojis.
Clearly, this bullish thrust was weaker than the one before.
This thrust upwards would have stopped out traders of the
earlier short Congestion Zone setup.
2. This strong bearish bar was in stark contrast with the two
bullish Dojis preceding it. It was an excellent setup bar for the
bearish Deceleration pattern and re-entry of the short
Congestion Zone setup.
Overall, this was a great short setup.
Analysing Probable Targets
Now, let’s take a look at our target options for this setup. To do
that, we need to take a look at the larger picture in Figure 5-58
below.
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3. Potential new
bearish channel
1. From this
bearish
thrust, we
projected a
target here
2. From this more recent
downthrust, we projected
another potential target
Target B
Target A
Figure 5-58 Considering two projected targets
1. From this five-bar bearish thrust, we projected Target A.
2. From this more recent four-bar downthrust, we projected
Target B, a more conservative target.
(Note that we did not consider the three-bar thrust in the middle
of the chart. That was because the market had already breached
the corresponding target.)
3. As mentioned earlier when we introduced price channels, it is
useful to anticipate potential channels to employ them in the
targeting process. Here, the two arrows point to the potential
bear trend line and channel trend line respectively. This
potential channel would become the effective channel once the
market pushed down to a new low.
(The current effective bear trend line is faded as a dotted line.)
The most important observation here is that Target B was within
the potential bear channel, while Target A was beyond it. This
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means that Target B was far more likely to be achieved
compared to Target A.
Hence, Target B was our selected target.
However, that might change because the bear channel trend
line offered a moving target. A bearish channel is a downwards
sloping line which offers a more ambitious target with each new
price bar. Hence, we might get a chance to aim more
aggressively.
But for that, we’ll see.
Evaluating the Expectancy
The last step is to evaluate the setup expectancy. With a bearish
bias and an excellent short setup, it was likely that the market
would hit Target B before hitting our stop-loss.
If the probability of this trading setup was 40%, should we take
the trade?
Figure 5-59 below shows the answer with the R2R indicator.
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1. This was our
short setup bar
2. Target B was below
the R2R marker
Target B
2. Required target level
for positive expectancy
Target A
Figure 5-59 Expectancy analysis for the Deceleration setup
1. This was our short setup bar.
2. For that setup bar, this was the minimum target for positive
expectancy, assuming a 40% win rate.
3. Since Target B was lower than the minimum required target
for this short setup, we had a positive expectancy setup.
Let’s see what happened with this trade in Figure 5-60 below.
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1. Short setup bar
2. This bar hit both
targets and tested the
channel trend line
Target B
Target A
Figure 5-60 Projected targets hit
1. This was our short setup bar, for visual reference.
2. The market went straight for our target. This bar was critical
as it hit both targets and tested the channel trend line all at
once.
To appreciate the value of a price channel in our target
evaluation, we need to zoom out and look at what happened
after our target was hit.
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2. After the market bounced
up from the channel trend
line, it never looked back
1. We exited here
Target A
Target B
Figure 5-61 Ignoring the confluence of targets was a bad idea
Figure 5-61 shows the entire bearish trend and ended with the
last 1-minute bar of the session.
1. This was where we exited.
2. The market found support at the channel trend line to the
exact tick. Then, it bounced up and never looked back. By the
end of the session, the market has retraced around half of the
prior downtrend.
This example demonstrates the effectiveness of a channel as a
target. But in this case, this support area was particularly potent
because there was a confluence of the channel trend line with
two thrust-projected targets (Target A and B). To ignore it
would be foolhardy.
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5.3 - Managing Trades for Positive
Expectancy
In our earlier discussion of stop-losses and profit targets, we
came across the concept of active trade management. Active
trade management involves one or more of the following
actions.



Adjusting the stop-loss order
Adjusting the target limit order
Exiting at the market with a reversal signal
My recommendation was that active trade management should
be reserved for advanced traders who are capable of reading
price action confidently without being affected by their P&L.
If you decide to start experimenting with active trade
management, pay attention here. In this section, we will discuss
the correct mind-set of active trade management.
In order to manage your trades effectively, remember that what
you are trying to achieve is, ultimately, positive expectancy.
Hence, each decision taken to actively manage your trades must
make sense in the context of achieving positive expectancy.
Before you decide to adjust your stop-loss order and/or profit
target order, you should go through the same thought process
you go through when considering a new trading opportunity.
You should adopt the following steps.
1. Consider the target and stop-loss level you intend to
adjust to.
2. Determine if the market is likely to hit the intended target
before hitting the intended stop-loss level. (Estimate
probability.)
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3. Work out the new reward-to-risk ratio.
4. Evaluate if the adjustments to the stop-loss and target
orders would improve the expectancy of your position.
In other words, would you enter a fresh trade at the current
market price, given the current price action context, with the set
of target and stop-loss levels you intend to adjust to?
Let us drill deeper into this concept with an example. With the
help of Figure 5-62, let’s work through the thought process of a
stop-loss adjustment.
Original stop-loss
Intended stop-loss
1. Short Congestion
Break-out Failure setup
Current price
2. Considering a stop-loss
adjustment at this point
Target (Unchanged)
Figure 5-62 Considerations for tightening a stop-loss order
1. We shorted based on this Congestion Break-out Failure setup.
The stop-loss order was placed a tick above the setup bar. The
horizontal line at the bottom of the chart represents a target set
with the low of the previous session.
2. At this point, the market made a new low. We considered the
possibility of tightening our stop-loss to the level marked as
“Intended stop-loss”.
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The question we need to ask ourselves is this.
Would we enter a new short position at the current price with
the intended stop-loss and the same target? Would such a trade
offer positive expectancy?
If the answer is yes, then we should adjust the stop-loss.
The above explains the correct motivation for adjusting our exit
orders. The consideration for exiting at the market before any of
our exit orders are hit (stop-loss or profit target) is slightly
different. We should exit at the market if both conditions below
are met.


Our assessment of price action tells us that our current
position is no longer one that offers positive expectancy.
There is no way to adjust our stop-loss or target orders to
preserve a state of positive expectancy.
The above sounds great in theory but is difficult to put into
practice. This is why active trade management is an advanced
technique. However, it is critical and extremely useful to
remember that the objective of any trading decision including
active trade management is to achieve positive expectancy.
We do not tighten our stop-loss so that we get to breakeven.
We do not bring our target closer so that we can feel like a
winner.
We do not push our target further so that we can make up for
earlier losses.
This is because none of these reasons have anything to do with
positive expectancy.
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We should only actively manage our trading position for the
purpose of increasing its expectancy or avoiding a position of
negative expectancy.
Let’s take the practice of taking partial profits as an example.
If you trade more than one contract, you have the option of
taking partial profit by exiting part of your position.
But why does a trader take partial profits? Does it improve the
expectancy of the trade?
Most traders do not consider this question when they exit
partially. They just want to feel good about having some profits
in their pocket without considering the impact on expectancy.
Let's say you entered with two contracts at 1000. You exit one
contract at 1005 and one contract at 1010.
Conceptually, you are engaging in two trades.


First trade – Entry: 1000 & Exit: 1005
Second trade – Entry: 1000 & Exit: 1010
With hindsight, we know that the second trade gave a better
outcome. However, in real-time, we could only assess
expectancy. Which trade had higher expectancy?
If the first trade enjoyed higher expectancy, then you should
have closed both contracts at 1005.
If the second trade had higher expectancy, then you should
have exited both contracts at 1010.
Why split them up?
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This is why I do not see a need for taking partial profits.
As I mentioned, conceptually, taking partial profits is like taking
two (or more) different trades at the same time. In that case, I
need to assess the changing market conditions with respect to
multiple trades concurrently and that complicates my analysis
process. I would rather spend my effort on analysing one trade
well and focus my position size on it.
Of course, practices like moving your stop-loss order to
breakeven and taking partial profits have psychological benefits.
They help to make you feel safe, and feeling safe might put you
in a better state of mind to trade.
But what you need to understand is that these psychological
benefits have a cost, in terms of trade expectancy. Whether or
not these benefits are worth the cost, I’ll leave you to decide.
“Successful farmers don't plant a crop and then dig it up
every few minutes to see how it is doing. They let it
germinate, let it grow.
Larry Williams, Long-Term Secrets to Short-Term Trading
5.4 - Conclusion
This chapter is the closest I can bring you to the thought
process underlying live trading.
This is the only chapter with examples of entire trades. We have
pieced together everything we have learned so far and
completed the journey from analysis to trading.
Trading is not about picking a setup and clicking a button. It
involves market analysis with different objectives and putting
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these analyses together to find trading opportunities that offer
positive expectancy.
The framework we have gone through is useful for a
discretionary trader. We use objective tools (trend lines, pivots,
price patterns) and interpret them to arrive at subjective
decisions regarding the market bias, our potential stop-loss and
target level.
Then, we exercise our judgement to estimate the most
important piece in the puzzle of discretionary trading –
likelihood of winning.
Finally, we plug all these pieces of information into the
expectancy formula to determine if the trading opportunity is
worth our effort.
This thought process emphasises the interplay between
objective trading tools and subjective interpretation, and brings
the concept of positive expectancy to the foreground. Even if
you do not employ the exact price action trading techniques
described, this thought process remains applicable.
ACHIEVING POSITIVE
EXPECTANCY

Learn to decide if a trade offers
positive expectancy in a split second

Write down your ongoing analysis

Manage trading positions to increase
or maintain expectancy
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Chapter 6 – The Analytical Cycle
We have learned how to judge the market bias, find setups and
targets, and how to integrate them together to decide if a trade
is worth taking. If you’ve understood the complete examples in
the last chapter, you can easily practise these skills with your
own charts with historical price data.
However, in real-time trading, when your charts are constantly
being updated with new price bars, do you know what to do?
The actual process of market analysis is an active process. We
do not stare at the screen aimlessly until a setup appears, and
simply click “buy”. We need to constantly evaluate the market
bias, look for setups, and consider potential targets. It is an
ongoing process.
Evaluating the market bias always comes first. Then, constantly,
we need to keep a lookout for signs that the market bias has
changed. This is the most important goal. After we have
deciphered the market bias, we start looking for trading
opportunities.
To find trading opportunities, we need to pay attention to
potential setups and targets concurrently. We need to pick out
pairs of stop-loss point and profit target, and ask ourselves if
the market is likely to hit the target before the stop-loss.
That’s not the end. We will need to evaluate if our assessment
of the winning probability and the reward-to-risk ratio offers
positive expectancy. Luckily, we have the R2R indicator to
simplify this step.
However, it remains that you have a boatload of tasks on your
mind. And, this is only the first aspect of your analysis.
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The second aspect involves reviewing our trading premises,
trading records, and trading results. By analysing them, we try
to find out what is working and what is not. The aim is to
understand, verify, and improve our trading edge.
It is clear that as traders, we need to perform two types of
analysis. The first is the analysis of the market to identify
trading opportunities. The second is the analysis of our trading
records to improve our trading performance.
Most traders understand these two types of analysis and their
objectives. However, they treat them as distinct activities and
fail to appreciate the relationship between them. To achieve the
best trading performance, it is essential to understand how
these two types of analyses influence each other.
Hence, in this chapter, we will introduce the Analytical Cycle to
close this gap. This cycle offers a systematic guide for
implementing and improving your trading edge.
The Analytical Cycle is a five-stage process with dual objectives.
Figure 6-1 illustrates the cycle.
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Figure 6-1 The Analytical Cycle (solid steps and dotted goals)
The solid boxes contain the actions we need to take within the
cycle. These five steps go through a feedback loop. The first
step is to establish our trading rules and guidelines. The last
step is to refine them before going through the cycle again.
This cycle has two objectives which are highlighted in the dotted
box. The objectives are:
1. Trade consistently while keeping your emotions in check.
2. Verify and improve your trading edge.
In the following sections, we will elaborate each step of the
process. We will discuss how to perform them correctly, so that
we achieve our two objectives.
The Trading Toolkit included is useful for working through the
Analytical Cycle.
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6.1 - Establish Rules and Guidelines
To manage our analysis in a systematic and efficient manner,
we need a set of trading rules and guidelines. Hence, the
Analytical Cycle starts from establishing our trading rules and
guidelines to aid our market analysis. In this stage of the cycle,
we aim to consolidate what we have learned about market
behaviour and price action into written principles to guide our
analysis.
Before we start making a list, we must first understand the
difference between rules and guidelines.
Trading rules must not be broken under any
circumstances. Due to their absolute nature, having rules
prompt action without deliberation. Thus, they help to enforce
discipline and encourage swift decision-making. A key benefit of
having trading rules is ensuring the consistency of your trades.
For instance, you have a trading rule stating that you must take
setup bars that close in the direction of your intended trade.
According to that rule, you must never buy above a bearish bar
or sell below a bullish bar. You cannot exercise any discretion
here. Hence, you do not need to consider the validity of the
setup bar on a case-by-case basis. As a result, you are able to
make trading decisions swiftly.
Trading rules can encompass all aspects of trading including the
instrument to trade, the time frame, the time period, trading
strategies, and trade management methods.
Trading guidelines can be broken with justification.
Remember the bending of rules we discussed in the last
volume?
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Guidelines are “rules that we can bend”. Essentially, guidelines
offer room for us to exercise our discretion and potentially
achieve better trading results. The drawback is the additional
analysis we must perform each time in order to justify breaking
a guideline.
For instance, a guideline states that long setups should only be
taken if the market is in a support area. Thus, generally, you
should look out for long setups only when the market has
retraced down to a support area. However, when the market
bias is clearly bullish and the long setup looks particularly
strong, you might decide to ignore the guideline and take the
long setup even if the market has not fallen back to a clear
support area.
Of course, guidelines should not be broken according to your
whims and fancies. You need to justify any deviation.
RULES VERSUS GUIDELINES
Never break rules; Break guidelines for
good reasons
Neither rules nor guidelines are fixed permanently. Both are
subject to review. Rules and guidelines can be altered, added,
or removed. A rule can become a guideline, and likewise a
guideline can later be encoded as a rule. However, again,
changes to trading rules and guidelines should not be arbitrary.
How do we know when to change our trading rules and
guidelines?
We let the Analytical Cycle guide us in our review of trading
rules and guidelines. In the subsequent steps of the Analytical
Cycle, we will collect information to keep track of the
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effectiveness of our rules and guidelines to justify any changes.
By adjusting our rules and guidelines with informed decisions,
we move towards our goal of improving our trading edge.
It is a trader’s personal responsibility to create trading rules and
guidelines based on what he has learned and to refine them
over time. Recall what you have learned from your own trading
experiences, this book, and other educational materials you
have studied. Then, start making your own trading rules and
guidelines. It will always be a work-in-progress.
In the Toolkit, you will find a sample list of trading rules and
guidelines for new traders. You may use it as a basis or an
example for your own trading rules and guidelines.
When creating your rules and guidelines, there are several
guiding principles to bear in mind.
Your trading rules and guidelines should reflect your
market beliefs and trading style. For instance, if you believe
that your trading edge stems from trading market trends, you
should have a rule of trading only when the market is trending.
And of course, for any sane trader, taking a trade only when
you perceive positive expectancy is certainly a trading rule.
Your trading rules and guidelines should also reflect your
level of experience, and the level of discretion you are
prepared to exercise in your trading. We have discussed the
subject of exercising discretion in trading in the last volume, and
I emphasised that the level of discretion a trader should
exercise depends on his or her trading proficiency. Thus,
beginners should definitely start with more rules and less
guidelines. As they gain experience and get better at
interpreting price action, they can convert some rules to
guidelines. Experienced discretionary traders tend to have more
guidelines than rules.
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Your trading rules and guidelines should strike a balance
between efficiency and efficacy. Trading rules are rigid but
they enable efficient decision-making. We know exactly what we
need to do or cannot do. We do not need to over-think.
However, rigid rules might throttle our trading performance.
On the other hand, guidelines offer us a solid basis to exercise
our judgement and adapt our trading decisions to the changing
market. While guidelines might offer more room for better
trading performance, they require more input from the trader.
Hence, guidelines slow down our decision-making.
To summarise, trading rules narrow our battlefield and
guidelines empower us to use the right weapon for each battle.
Having clear trading rules and guidelines is critical to a
systematic trading process.
TASKS – STAGE ONE
1. Review your trading style, beliefs, and
experience
2. Refer to the sample trading rules and
guidelines in the Toolkit
3. Write down your own trading rules
and guidelines
6.2 - Record Ongoing Analysis
With the trading rules and guidelines in place, we can then start
to analyse price action in real-time.
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In this section, we will explore a structured approach that uses
written analysis to focus our attention, control emotions, and
build confidence.
Together with the trading rules and guidelines, this approach
will help you maintain a consistent and unemotional perspective
of price action.
In addition, the written analyses will form an important part of
your trading records which you will review to verify and improve
your trading edge. More about this in Stage Four of the
Analytical Cycle.
6.2.1 - Thought Process for Basic Analysis
First, let’s go through the basic process of ongoing price analysis
and how to record it. Then, we will have a deeper discussion of
using written analysis to help us deal with the emotional and
confidence issues in real-time trading.
The constant process of price action analysis follows a simple
four-step template.
1. Identify the current price action feature. Describe what
you see.
2. Understand what it means. Does it show momentum?
Does it show selling pressure? Does it imply support?
3. Integrate it with prior analysis. What is the price action
context? What is the market bias?
4. Decide its impact on our potential actions (if any). Do you
buy or sell? Do you wait for further price action?
In a nutshell, focus on the current price action and integrate it
with past price action to form expectations of future price
action.
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It is an active process of extracting value from our observations.
Each observation results in:


A trading action (enter, exit, adjust positions); and/or
An idea of what to look out for to confirm or refute our
market hypothesis.
Let’s go through some examples.
Bearish Momentum
1. Identify a tested low that cleared below the previous
swing low.
2. Understand that it means bearish momentum.
3. Consider it within the context of a bullish market.
4. Decide that you will hold off long setups until there are
more bullish signs.
Merged Congestion
1. Identify price moving up into and congesting within a
Congestion Zone, forming a Merged Congestion Zone.
2. Understand that a Merged Congestion Zone is a
significant resistance.
3. Consider that the market has just formed a bearish Anticlimax pattern.
4. Decide that you exit from your long position.
Deceleration Pattern
1. Identify a bearish Deceleration pattern.
2. Understand that it means that the short-term buying
interest is not forthcoming.
3. Consider that the market bias is bearish and the
Deceleration pattern ended in a resistance area
(Congestion Zone).
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4. Decide to enter a short position. (Assuming that
expectancy analysis is positive.)
In fact, we have already seen dozens of such examples
throughout this book, especially in the complete examples in the
previous chapter.
The process of price analysis would have guided us to think
through the following:



Reasons for entering the trade
Reasons for adjusting our stop-loss/target orders
Reasons for exiting the trade
We always start our analysis with observing the current price
action. And we end our analysis by concluding its impact on our
trading actions. These actions include sitting on our hands, or
entering, exiting, and managing a trade.
By following this four-step process (identify-understandintegrate-decide), we ensure that every action we take is
backed by our interpretation of price action.
6.2.2 - Written Analysis as a Tool
Analysing price action as it forms is a very different exercise
compared to looking for historical trading setups. There are two
important aspects of live real-time trading that are missing
when we study historical price action.
The first aspect is the emotional woes. We might feel anxious to
trade. We might feel that we are missing out on the next big
move if we do not enter. Such feelings of anxiety and sense of
urgency are absent when we review historical data. In actual
trading, these emotions will push us into seeing trading
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opportunities when there are none. The result is overtrading,
one of the worst sins among day traders.
The second aspect is the lack of confidence in your analysis.
With some training, most people can analyse and explain a
historical chart. However, trusting your own real-time analysis
requires solid trading experience. If you are not confident of
your own analysis, you will hesitate to act on the trading
opportunities despite identifying them. In that case, you will
never realise the full potential of your analyses.
The best way to handle these difficulties is to write (or type)
your ongoing analysis. Writing encourages objective analysis.
The written records of your analysis also serve as a valuable
resource for your review in later stages of the Analytical Cycle.
WRITING IT DOWN
Writing down your analysis encourages
objectivity and helps in reviewing
The four-step process explained in the last section is not merely
a mental exercise. You need to expand it into a writing exercise.
Keep Emotions in Check
As you analyse the market, write down your assessment of the
market bias. Write down if there is a trend line supporting the
market bias. Write down if the momentum is aligned with the
trend line. Write down what are the trading setups telling you
about the market bias.
Write down your evaluation of possible targets. Write down the
confluence of target levels above and below the market price.
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Write down if the setup you are looking at is a high-quality one
and explain why.
Write down what would make you buy. Write down what would
make you sell.
Write down why you plan to deviate from your trading
guidelines. This will help to ensure that you are not abusing the
trading guidelines.
Writing down your analysis forces you to think about price
action seriously. It holds you accountable and prevents
emotional reactions to the market. Thus, write as though you
are writing a report for your boss. Be serious.
However, your boss happens to be one that does not care about
your grammar or your presentation format. Your boss does not
mind even if you just scribble on your draft paper. You can write
or type, whichever is faster for you. You need not write in
complete sentences. While writing your analysis is important, it
should never get in the way of your trade execution. If
necessary, come up with your own abbreviations to facilitate
swift recording.
Writing down your analysis is the single most powerful way to
help you tell apart your subjective analysis from your emotional
whims. Yes, of course your analysis is subjective. It is your
analysis. Subjectivity is not bad. Subjectivity is inherent to
judgement and evaluation. Good judgement leads to good
results. Bad judgement leads to bad outcomes. And all
judgements are subjective.
While subjectivity is not a problem, emotional decisions are. By
writing down why you decide to take a certain course of action,
you avoid making emotional decisions. Or at the very least, you
are fully aware that you are making an emotional decision.
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“Because of the bullish momentum shown by the tested low just
now, I should not be shorting until bearish momentum takes
control.”
If you had just written the above and are now staring at it, the
likelihood of you taking a short position without proper
justification decreases.
And even if you do proceed to take a short position, you know
that your actions have deviated from your analysis. The problem
is psychological. We tend to be in denial about psychological
issues, but having your written analysis in front of you makes it
a lot harder to lapse into denial.
“Price is bouncing off a bull trend line with a bullish Deceleration
pattern. Setup bar is a bullish reversal bar rejected by a
Congestion Zone. Good long setup. Potential target at the next
higher resistance coincides with the thrust-projected target. It is
likely that the market will reach the target before hitting the
stop-loss below the setup bar.”
You wrote the above and proceeded to take a long trade.
However, you got stopped out within the next two bars.
Does that mean that it is a bad trade?
No.
Should you feel bad about it?
Absolutely not.
This is because you had a good basis for taking the trade. The
quality of a trading opportunity is determined before the entry
and not after the exit. You have already concluded that it is a
good setup before you entered. Regardless of the outcome of
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the trade, the fact remains that it is a good trade. Your written
analysis reminds you of this probabilistic nature of trading.
The process of writing your analysis offers a constant reminder
that you are not a gambler. Your sole aim is to take good trades
(i.e. trades with positive expectancy), and not to feel happy
over individual winning trades or disappointed over each losing
trade.
“One reason why assignment writing is especially demanding
is that it forces you into a deep and powerful kind of
learning.”
Ellie Chambers and Andrew Northedge
The Arts Good Study Guide
Build Confidence in Your Trading Skills
Writing down your price action analysis ex-ante is also the key
to building confidence in your trading skills. To achieve this
objective, as you record your observations of price action, you
must also write down your corresponding expectations.
Write down what you think will happen next. Write down what
you think might not happen. Write down what you think might
happen if what you think might not happen eventually happen.
You get the idea.
Write down the kind of price action that will confirm what you
think. Write down the kind of price movement that will refute
your current market view.
You are never always correct. If you cannot think of any price
development that can refute your market view, you basically
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think you cannot be wrong. When you think that you can never
be wrong, you are in great danger.
Writing down your expectations is an important step in honing
your trading skills and gaining confidence in reading the market
in real-time. Figure 6-2 shows the ideal recording-learning cycle.
Record ex-ante
Price Action
Observation
Expected
Outcome
Record
ex-post
Actual
Outcome
Improve skills and
gain confidence
Figure 6-2 Learning cycle for real-time price analysis
Start with recording your observation of price action. For
instance, you observe that price is moving down towards a bull
trend line sluggishly without momentum. You record this
observation.
Together with that observation, you also record what you
expect the market to do. Let’s say you expect that price will
bounce up from the bull trend line. This process corresponds to
the four-step process discussed earlier.
Then, you pay attention to the actual price action. When the
market finally reaches the trend line, it forms a bullish reversal
bar and rises to a new high. You record this too.
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At this point, you are able to compare your expected outcome
with the actual outcome and note down the extent to which they
coincide or differ.
This process is not limited to your analysis of trading setups. It
should extend to every piece of significant price action that you
observe. After completing this cycle for a number of times, you
can evaluate if the market usually does what you expect it to do
based on your observations and interpretations.
If it does, you will gain confidence in your ability to interpret
price action in real-time. You should aim to keep objective
records. Write down your observation and expected outcome
ex-ante, and record the actual outcome ex-post. With objective
records of your expectations and the actual outcome, you can
learn to trust your analysis without subjecting yourself to
confirmation bias and overconfidence bias. The quality of your
trading records will determine if your confidence is justified.
Confidence developed this way is healthy and not misguided.
I must emphasise the importance of writing down your
observation and expected outcome before the actual outcome
emerges. Without doing that, it is too easy to lapse into a selfdeceiving state of mind that encourages denial and distortion of
memory. The hindsight bias (or creeping determinism) is wellestablished. It refers to the tendency to falsely claim that you
knew it all along only after the outcome emerges.
You see the market moving in a certain manner, and you
convince yourself into thinking that you expected it. But the
reality is that you saw the outcome, and then looked for signs to
confirm your thinking. This self-delusional process might keep
you going for a while, but it is not at all sustainable or
profitable.
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On the other extreme, the records might show that the market
does not do what you expected it to. In that case, the records
will provide you with valuable information to help you improve
your price action reading skills. For instance, through the
records, you realise that whenever you anticipated a change of
the market bias, you were wrong most of the time. This means
that you should consider waiting for more confirmation before
concluding a change of market bias. Without a clear record of
your analysis, you will not be able to come up with any concrete
steps for improving your trading skills.
You might be a price action genius. You might also be a reckless
trader who has no clue of how to perform price action analysis.
In any case, you are always better off knowing which one you
are.
“If someone is able to show me that what I think or do is not
right, I will happily change, for I seek the truth, by which no
one was ever truly harmed. It is the person who continues in
his self-deception and ignorance who is harmed.”
Marcus Aurelius, Meditations
6.2.3 - Tools for Recording
To get started with writing down your analysis, refer to the
Toolkit where you will find an Analysis Matrix that breaks down
the objectives and contributing factors of ongoing analysis.
Other than written analysis, a screen capture of the chart
containing each trade is also essential. Most charting platforms
offer the ability to save the chart image. If not, there are
several great note-taking software that you can use to capture
screenshots easily. (Refer to the Toolkit for recommendations.)
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An alternative to written notes and chart images is to capture
your trading process with a screen-recording software. You can
also narrate your analysis as part of the video. Recording your
trading process as a video offers the several advantages.
By replaying your trading process, you can simulate your
analysis and emotions during the trading process. This
simulation process is very useful for an in-depth study of an
individual trade. A video also captures the speed of the market
(intra-bar), an aspect that static chart images are unable to
retain.
However, ultimately, we always need to review a sample of
trades, and not any one trade, to arrive at constructive
conclusions. For reviewing a set of trades, it is more efficient to
scan through written analyses and chart images than replaying
dozens of videos and noting down their similarities and
differences.
Other than our price action analysis, after each trade, we must
record its outcome, together with its basic details.
These details include:







Traded instrument
Entry and exit time
Entry and exit price
Outcome (Net profit)
Direction of trade (Long/short)
Position size
Commissions and other trading costs
Your broker or clearinghouse records the trade details above
automatically as they are essential for processing your trades.
Your trading platform might also store a copy locally on your
computer. Hence, you do not need to trouble yourself with
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recording them while trading. You can easily retrieve these
records after each trading session and compile them for further
analysis. Thus, you just need to familiarise yourself with the
level of trade details required and the process of retrieving this
information.
In the Toolkit, you will also find a Trade Records worksheet for
recording this information.
TASKS – STAGE TWO
1. Practise analysing real-time price
action with the four-step process
2. Write down your analyses in the
Analysis Matrix, in real-time as well
3. Fill up the Trade Records worksheet in
the Toolkit
6.3 - Classify Trades
Armed with a multitude of trading records, you might be
tempted to start examining them for clues to avoid losses and
increase your trading profits.
Hold on.
Do not rush into analysing your trade records without first
organising them. Before you can conduct any form of
meaningful analysis with your trading records, you must first
classify them. This classification is a critical step that traders
often neglect.
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To classify your trading records, rely on the rules and guidelines
you established in Stage One of the Analytical Cycle. Essentially,
separate trades that comply with the rules and guidelines from
those that do not.
Relying on our trading rules and guidelines, we can separate our
trades into three types. Table 6-1 sums it up.
Type
Rules
Complied
Guidelines
Complied
Guidelines
Justified
Consistent
Yes
Yes
N/A
Discretionary
Yes
No
Yes
Yes
No
No
No
No
No
No
Yes
N/A
Rogue
Table 6-1 Trade classification
If you had followed your trading rules and guidelines
completely, the trade is consistent.
Rules are sacred. The moment you break a trading rule, the
trade becomes a rogue trade.
However, if you violate a guideline, your trade might be
discretionary or rogue. If you can justify it with price principles,
you have made a discretionary trade. If you cannot, the trade is
rogue.
For instance, your guidelines state that you should take only
long setups that overlap with a support level. However, you took
a long setup that did not overlap with a support area because
you had not taken a single trade in the session and were feeling
impatient. That is a rogue trade.
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On the other hand, if you took the setup because you noticed a
confluence of setups (for e.g. Deceleration and Pressure Zone),
you have a valid reason for ignoring the guideline. In this case,
the trade is discretionary.
This three-group classification is extremely important for trade
analysis. By studying the group of consistent trades, we are able
to examine the soundness of our trading rules and guidelines.
By looking at the group of discretionary trades, we are able to
measure the effectiveness of our discretionary trading skills. By
analysing our rogue trades in a separate group, we are able to
isolate the quality of our analysis from the strength of our
trading psychology.
Tagging each trade as one of the three types above lays the
foundation for measuring our trading edge and identifying the
areas that are lacking.
For instance, after collecting a large sample of trades, you find
that your set of consistent trades is profitable but your
discretionary trades are barely profitable. You can then
reasonably conclude that you have sound trading rules and
guidelines, but your trading gut needs further honing. It
probably implies that you should turn some guidelines into
rules.
In addition, your rogue trades are showing overall losses. Thus,
it is undeniable that rogue trades are damaging your
profitability. It offers strong motivation to work on your trading
discipline.
Classifying a trade as consistent is straightforward. The tricky
part is in differentiating between a discretionary trade and a
rogue trade. Very often, we distinguish a discretionary trade
from a rogue trade by a valid explanation for violating a
guideline.
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For example, let’s use the same guideline that you should only
take long setups that overlap with a support area. You took one
that did not.
The reason is that it was a re-entry equivalent trade (of an
earlier Trend Bar Failure setup) and was a Deceleration setup at
the same time. Since a re-entry equivalent is usually more
reliable and having a confluence of setups is also a sign of a
high quality setup, the guideline violation seems justified.
Hence, the trade was a discretionary one.
However, there is no clear answer key for reasonable
explanations of guideline violations. Furthermore, in most cases
(unless you work with a trading partner or mentor), you offer
the explanation, and you decide if the explanation is valid.
Clearly, this is a problem.
In other words, we are the problem. Since we are both
answering and judging the answer, it is easy for our minds to
play tricks on us. These tricks would cause us to recognise a
rogue trade as a discretionary trade or vice versa.
Why would we recognise a rogue trade as a discretionary trade?
One reason is that we do not want to admit that we have taken
an inconsistent and emotional trade. Hence, we force feed
ourselves some irrational justification and accept a rogue trade
as a discretionary one.
Another reason is that the trade turned out to be profitable. If
we classify it as a discretionary trade, it means that we can take
credit for it. We would feel good.
Why would we recognise a discretionary trade as a rogue trade?
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The common reason is that the trade turned out to be a loser.
We do not want to admit that our trading technique is faulty.
We would rather push the responsibility to a momentary lapse in
discipline. In that way, we can protect the effectiveness of our
trading strategy, at least in our minds.
Clearly, the outcome of each trade offers incentive for us to
overlook facts and erroneously classify our trades. We want to
take credit for trades that went well and dissociate ourselves
from those that brought us losses. As a result, it is difficult for
most traders to distinguish rogue trades from discretionary
trades.
Fortunately, we already have an excellent solution to this
problem. We write down our ongoing price action analysis to
justify our trades. The key point here is that we write them
before we know the outcome of each trade. These ex-ante
written analyses are critical in an objective classification of our
trades.
We have our trading rules and guidelines. And we have already
analysed the price action according to our rules and guidelines
before deciding to take a trade. The answer to whether each
trade is consistent, discretionary, or rogue can be answered at
the point when we decide to take each of them.
Hence, we should classify each trade before we know its
outcome. In doing so, we ensure that the trade outcome does
not taint our classification. The ex-ante written analysis makes it
possible to do so.
EX-ANTE CLASSIFICATION
Classify a trade as consistent,
discretionary or rogue once you decide
to take it, before you know its outcome
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However, there is one exception to the ex-ante classification
rule. It is when we break our trading rules or guidelines after
our trade entry. The best example is the breaking of our exit
rule. For instance, we shifted our target without justification
after our trade entry. In that case, we need to change our
classification ex-post to mark the trade as a rogue trade.
At this stage, we are able to appreciate how all steps of the
Analytical Cycle tie in together. The rules and guidelines and the
ongoing written analysis not only help us trade better, they are
also the key to a proper trade classification that will eventually
enable a meaningful trade review.
In the Trade Records worksheet (in the Toolkit), there is a
column for classification. You can classify each trade by
choosing one of the options: Consistent, Discretionary or Rogue.
TASKS – STAGE THREE
1. Understand the difference between
Consistent, Discretionary, and Rogue
trades
2. Classify them as soon as you decide
to take the trade
3. Label the trades in the Trade Records
worksheet
6.4 - Review Trading Records
In this final stage, you will use the trade records you collected in
the earlier stages to answer a few important questions.

Do you have a trading edge?
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

What size should you trade? (This depends on your
maximum drawdown.)
How can you improve your trading?
To answer them, you will conduct simple statistical analyses
with your Trade Records. At this point, I must reiterate the
importance of keeping objective and detailed Trade Records.
This is because you will rely on them to answer the three key
questions above. Remember “garbage in, garbage out”.
After answering them, we will revisit our trading rules and
guidelines to refine them. Using these improved rules and
guidelines, we will work our way through the Analytical Cycle
again, and again. Ideally, each cycle is based on an improved
set of trading rules and guidelines.
6.4.1 - The Holy Grail
Before we dive into the technicalities of reviewing our trade
records, let’s take a look at the main obstacle that plagues the
review process - the problem of the Holy Grail.
As briefly discussed earlier, when we review our trades, we tend
to allow their outcomes to affect our review. (This is the issue of
ex-ante versus ex-post.) This is a common yet often ignored
problem.
When we encounter a winner, we tend to think that our analysis
was good.
When the trade turns out to be a loser, we think that we must
have overlooked something important. Hence, we must find out
what we had overlooked, so that we can avoid losing in the
future.
What is wrong with thinking this way?
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There is nothing right about it.
First, it highlights a lack of understanding of the probabilistic
nature of trading. It assumes that a winning trade is a good
trade and a losing trade is a bad trade. These assumptions are
plain wrong in a probabilistic game like trading.
Desirable trades are trades that have a positive expectancy.
Positive expectancy trades are trades that are expected to
produce positive profits over a large sample of trades.
As for an individual trade with a positive expectancy, it can be
either a winning or losing trade. The same goes for trades with
negative expectancy. The key point here is that winning trades
are not always good trades.
Table 6-2 clarifies this point.
Positive
Expectancy
Negative
Expectancy
Winning Trades
Desirable
Undesirable
Losing Trades
Desirable
Undesirable
Table 6-2 What is truly desirable?
We should desire to find trades in the “Positive Expectancy”
column. This objective poses a problem to most traders because
it seems to imply that we must desire losing trades as well as
winning trades. Human nature dictates that nobody likes to lose.
Hence, most traders do not look for trades in the “Positive
Expectancy” column. Instead, they look for trades in the
“Winning Trades” row. This is commonly known as the quest for
the Holy Grail, which is time-consuming and entirely futile.
Why is looking for 100% winning trades a futile goal?
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Trades with positive expectancy share common price action
characteristics. For instance, they are in the direction of the
market bias and are found along support or resistance area.
Hence, by focusing on these common characteristics, we can
reliably choose trading opportunities that promise positive
returns for a large set of trades.
On the other hand, winning trades do not share common
attributes. You can win any trade within any market conditions
due to the element of luck. One winning trade might be going
along with the trend and another winning trade might be going
against it. There is nothing in common about them, except that
they both concluded with profits. If their profitable outcome is
the only similarity between them, it follows that we have no
basis to anticipate them. This is because we cannot use the
outcome of an event to predict the occurrence of that event
itself.
Let’s look at an analogy.
I want to cross the road without getting hurt.
I know that in order to cross the road without getting hurt,
generally, I need to look out for traffic on both sides, estimate
the distance and speed of oncoming vehicles, and cross with a
speed fast enough to avoid a collision. By implementing these
steps, I can cross the road each time knowing that most likely, I
will not be hurt.
These are crossings of positive expectancy. I might still get hurt
due to a million other reasons. I might faint in the middle of the
road because I didn’t eat my breakfast. I might get crushed by a
falling plane (absurd, but not impossible). I might have missed
an oncoming car. A driver with murderous intent might
accelerate beyond my expectations.
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Now, let’s say I want a 100% safety rate for my road-crossings.
I want to cross the road knowing that I will never ever be hurt.
To ensure that I will not faint in the middle of the road, I must
complete a health check-up just before I cross the road. To
ensure that no plane will fall on me, I must carry air radar
equipment at all times when I cross roads. These are absurd
solutions and even with them, it is impossible to completely
eliminate danger in crossing roads.
The only certain way to not get hurt when you cross a road is
not to cross it at all.
Looking for guarantees is not only a crazy idea in trading, but in
most things in life. Understand this before reviewing your trades
and learn to like losing trades with positive expectancy.
The wrong way to think:
When we encounter a winning trade, we think that our
analysis is good. When a trade turns out to be a loser, we
think that we must have overlooked something important.
Hence, we must find out what we overlooked, so that we
can avoid losing in the future.
The right way to think:
When we encounter a large number of trades that result
in positive returns, we should think that our analysis was
good. When a large number of trades produce losses, we
should find out the problem, so that we can avoid losing
in the future.
Isolated trades do not tell much. A sample of trades tells a
better story.
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Hence, there is no need to go through a review after every
trade. Due to the probabilistic nature of trading, studying trades
in isolation offers limited benefit. It is best to gather a set of
trades (at least across 30 traded sessions) before performing
your first review.
Subsequently, aim to review your trades weekly or monthly
depending on your trading frequency. Another option is to
conduct a review after a fixed number of trades. For instance,
review your records after every 30 trades.
6.4.2 - Measuring Expectancy
We have learned to assess trading opportunities to select those
that offer positive expectancy. Our objective as traders is to
take trades with positive expectancy. Ideally, every trade we
take should offer positive expectancy.
However, we cannot be absolutely certain that the expectancy
of each trade we take is positive. This is because a trade with
positive expectancy can be a winner or a loser. We will only find
out after a large number of trades over time.
This seems to imply that if we are profitable after taking a large
number of trades and after a long period of time, we must have
been taking trades with positive expectancy. That is not true.
Even if we are profitable in the long run, it does not mean that
all the trades we took had positive expectancy.
Theoretically, we can separate the large number of trades we
took into two sets.
1. Positive expectancy trades with $A profit
2. Negative (and zero) expectancy trades with $B losses
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The first set will, in aggregate, produce profits. The second set
will result in losses.
As long as the profits from the first set of trades exceeds the
losses brought about by the second set of trades (A>B), the
overall outcome of our trades will still be positive. In other
words, we took some desirable trades and some not-sodesirable trades, but the winnings from the desirable ones
exceed the losses we incurred by taking the bad ones.
Hence, even if we are profitable after a large number of trades,
we should not conclude that all of our trades had positive
expectancy.
What we know for sure is the outcome of each trade. We know
exactly if a trade is a winning one or a losing one.
What is not so clear but far more important is its expectancy.
Expectancy is a probabilistic concept, and we should not expect
a deterministic answer. However, it is such an important
concept to traders that we should at least attempt to estimate
it.
Measuring expectancy refers to verifying that we are taking
desirable trades with positive expectancy. This is the first
objective of this section.
As mentioned in our introduction, a casino does not only enjoy
positive expectancy, it knows that it does. As for traders, we
might or might not have a trading edge, and we are never
100% sure if we do. This is a serious handicap. If we are not
sure whether or not we have a trading edge, why are we even
trading? Hence, we must attempt to measure the expectancy of
our trades as a whole.
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There are many ways to measure the expectancy of our trading
methods. However, none of them offers absolute certainty. This
is something we must accept. Accept that no trading strategy
guarantees a trading edge. Hence, we must also decide how
certain we need to be before we trust a trading method
sufficiently to commit real financial capital to it.
Since no measurement method offers certainty, I prefer to use
one that is the most intuitive. The method I recommend is the
Monte Carlo simulation.8 You can trust it for two reasons. First,
it was developed by nuclear scientists (very smart guys,
basically). Second, when statisticians say “simulation”, they
usually mean Monte Carlo simulation. It is a standard.
This is how it works. Let’s say you have made 100 trades using
the price action techniques in this book. Using the 100 trades as
our sample, we pick a random trade.



Are we more likely to pick a winning trade or a losing
trade?
Are we more likely to pick a large winner or a small
winner?
Are we more likely to pick a large loser or a small loser?
All these questions depend on the sample. It depends on how
many winning and losing trades the sample contains and the
distribution of their magnitudes.
Ultimately, it boils down to how you traded.
If, in the 100 trades that you took, you ensured that your trade
risk never exceeded $150, then there is zero chance that we
would pick a losing trade with a loss greater than $150. As
another example, if you had more than 50 winning trades in the
For an alternative method to assess your trading edge, refer to the “R Multiple”
concept explained in Dr Van Tharp’s books.
8
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sample, then it is more likely that a random trade picked from
the sample is a winning trade.
Intuitively, the sample represents the profile of your trading
performance. Assuming that you will continue to produce trades
that are consistent with the ones in the sample, picking random
trades from that sample offers you a way to simulate your
future trades.
Why would you want to simulate your future trades?
Remember that your objective is to check if your trading
strategy has positive expectancy over the long run. If it does, it
should produce a net profit over a large number of trades.
Hence, if we can simulate taking a large number of trades
numerous times, we can more reliably evaluate if your trading
strategy offers positive expectancy.
This is where Monte Carlo simulation comes in useful. By picking
a series of random trades from your trading sample, you are
able to construct numerous sets of 100 trades. If most of these
sets of 100 trades are profitable, then you can be relatively
confident of your trading edge.
As we pick a trade out of the provided sample to simulate your
trading performance, we have the option of replacing it. If we
replace the trade into the sample, we would be able to pick out
the same trade again in a subsequent draw. If we do not, we
will pick out each trade once. In that case, we are merely
replicating the same 100 trades in a different sequence.
For assessing our trading edge, we must conduct the simulation
with replacement. The method with replacement introduces
greater uncertainty in the results. It allows us to err more
conservatively. Furthermore, we are interested in the
profitability of the simulated samples (i.e. the cumulative
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profit). If we were to simulate without replacement, the
cumulative profit of each random sequence will be the same as
that of the sample. It is ineffective for our purpose.
Note that there are dozens of caveats in using Monte Carlo
simulation. I will not elaborate on them. The method used here
strikes a balance between intuition and statistical reliability. It is
a suitable way to assess your trading edge without getting
mired in advanced statistical methods.
In the Toolkit, you will find a basic Monte Carlo simulation tool.
Refer to it as you read the following to learn how to use the tool
correctly.
To perform a Monte Carlo simulation, we need to provide three
inputs.
1. Sample of trades
2. The number of trades per sequence
3. The number of sequences to simulate
Figure 6-3 Monte Carlo Simulator inputs
Figure 6-3 shows a screenshot of the inputs section of the Monte
Carlo Simulator in the Toolkit.
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1. Start with a sample of at least 30 trades. The more, the
merrier. The simulation will draw the sample from the “Net
Profit Per Contract” column of our Trade Records.
2. For the number of trades per iteration, choose a reasonably
large number. It also depends on the time horizon you would
like to assess. For instance, if you want to find out the likelihood
of you being profitable each month, use the average number of
trades you take in one month.
3. The number of iterations to perform depends on the volatility
of your trade sample. Volatile samples require a higher number
of sequences. Performing more sequences is better but it could
be time-consuming.
A simple way to find out the suitable number of sequences is by
trial and error. Start with 1,000. Perform the simulation a few
times and watch how the results vary. If the results vary too
much, double the number of sequences to generate. Then,
perform a few simulations again and observe the variation in the
results. Keep increasing the number of sequences simulated
until the results are relatively stable.
To make sense of the simulated results, you need to decide on
how sure you need to be.
Do you want 100% of the simulated sequences to be profitable?
If 95% of the sequences show positive cumulative profits, is it
good enough for you?
How about 90% or 80%?
You must determine the level of certainty that is good enough
for you to risk your trading capital. Most statistical analyses are
satisfied with 95% as a threshold for certainty.
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Figure 6-4 Monte Carlo Simulator results
Figure 6-4 shows the results section of the simulator.
By entering 95% into the first box, it will show you the worst
return of the top 95% of the sequences. Essentially, it
disregards the worst 5% of the results.
For instance, if it shows $1,000, it means that for 95% of the
simulated runs, you earn at least $1,000 in cumulative profits. A
positive cumulative return means that you have a trading edge.
If it shows a cumulative loss instead of a profit, then you do not
have a trading edge.
For new traders, I suggest that you trade in simulation mode
until your trading records confirm that you have a trading edge
that you are comfortable with (e.g. 95% of the simulated trade
sequences are profitable).
You can also specify similar percentages for the number of
consecutive losses and maximum drawdown per contract. The
former will give you a sense of the number of consecutive losses
you need to prepare yourself for psychologically. The latter will
have an impact on your position sizing, a topic we will discuss in
the next section.
Our simulation uses “Net Profit Per Contract” as our input. The
underlying assumption is that every trade is taken with a single
contract. This assumption allows us to eliminate the impact of
position sizing on the assessment of our trading edge.
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Why is there a need to eliminate the impact of position sizing in
assessing our trading edge?
Position sizing is usually a function of the amount of trading
capital at our disposal.
For instance, some traders aim to risk 2% of their trading
capital for each trade. Let’s say you got a capital injection from
a family member. Naturally, you started trading larger positions
according to the fixed percentage model. At the same time, you
got lucky and had a winning streak. In that case, simulation
using “Net Trade Profit” would produce a high cumulative profit
figure.
However, the high figure is partly due to the larger position you
happened to be trading when you got lucky. It has nothing to do
with your trading edge. By taking “Net Profit Per Contract” as
our input, we are able to eliminate this impact.
However, some traders deliberately use position sizing to
improve their trading edge. They vary their position size
according to the assessed quality of each trading setup. They
attempt to increase their position size for a good setup and
decrease their position size for a less optimal one. If they are
able to correctly distinguish a good setup from a less ideal one,
this practice will contribute to their trading performance. If not,
it might harm their performance.
For these traders, they might want to analyse if their position
sizing efforts have given them an extra edge in their trading. To
do so, they need to use a simple tagging method which we will
explain later in the section under “Improving Expectancy”.
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6.4.3 - Computing Drawdown (for Position Sizing)
Assume that we have a trading edge. Do we then make full use
of it and start trading the maximum number of contracts we can
afford?
No. This is because even if our trading strategy has positive
expectancy, consecutive losses are possible. Streaks of losing
trades lead to drawdowns.
Drawdown is the peak-to-trough decline in your trading capital.
Look at Figure 6-5 for a chart that plots the balance in a trading
account against the number of trades taken. The drawdowns are
marked with red arrows.
Figure 6-5 All trading strategies produce drawdowns
I simulated this graph trading one contract with a trading
strategy that has equal likelihood of producing the following four
outcomes:

$-100
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


$0
$100
$200
The expectancy of each trade in this simulated strategy is
therefore:
(-$100 x 25%) + ($0 x 25%) + ($100 x 25%) + ($200 x 25%)
= $50
It is a trading strategy with positive expectancy. Nonetheless,
there would be drawdowns due to streaks of losing trades. To
ensure that we remain in business long enough to reap the
profits of this trading strategy, we must ensure that the
maximum drawdown of our trading activities does not ruin
our account.
The two key concepts are the maximum drawdown and the
account ruin point.
The maximum drawdown is the largest peak-to-trough decline.
For our example, the maximum drawdown is $400 as marked
out in Figure 6-6.
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Maximum drawdown is
$400 for one contract
Figure 6-6 The maximum drawdown in this case is $400
Now, let’s determine our account ruin point. The account ruin
point is different for every trader, depending on your agreement
with your broker and your trading strategy. Use the following
definition to figure out your trading account ruin point.
TRADING ACCOUNT RUIN
A trading account is ruined when it
cannot execute the minimum size for its
intended trading strategy
For instance, I have a day trading strategy for the NYMEX crude
oil futures market (CL). I use an all-in, all-out approach, so I do
not need to trade multiple contracts. The minimum size for my
strategy is 1 contract.
As a day trader, I avoid overnight margins. My broker tells me
that the day trading margin for the CL contract is $1,000 per
contract. For each round-turn transaction, the trading cost
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(commissions, exchange fees, etc) per contract is $5. Hence, if
my trading account falls below $1,005, I am unable to execute
my trading strategy.
Thus, my account ruin point is $1,005.
I have a clear objective. My trading account cannot fall below
this amount because I need to maintain the ability to trade.
Given a maximum drawdown of $400, I need at least $1,405 to
start trading. In that case, even if I experience the maximum
drawdown right from the start, my account balance will not fall
below the ruin point of $1,005.
According to the calculations, I need $1,405 to trade one
contract. Am I sure?
Not really. I am confident of my account ruin point because my
day trading margin and trading costs are certain. However, I am
not so sure of my potential maximum drawdown.
Using the same parameters as the trading strategy shown in
Figure 6-5, I performed a second simulation. The resultant
equity curve is shown in Figure 6-7.
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The maximum drawdown
is $600 for one contract
Figure 6-7 A larger maximum drawdown
Over the same number of trades, the maximum drawdown is
$600 this time round. Given a larger maximum drawdown, we
need more money in our trading account to start trading. In this
case, we need $1,605.
It is clear that we are uncertain about our maximum drawdown
even if we are certain that we have a trading edge. Given the
uncertainty in our future trading performance, how sure are we
that the maximum drawdown will not exceed $600?
The best way to find out is to repeat many sequences using the
Monte Carlo simulation. Other than simulating the expectancy
using our Trade Records, the Monte Carlo tool in the Toolkit also
calculates the maximum drawdown for each simulated
sequence.
Similar to the process for measuring expectancy, we need to
decide on the level of certainty we are comfortable with. If you
choose 95%, it will show you the worst maximum drawdown of
the simulated sequences after leaving out the bottom 5%.
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Let’s say you run 1,000 sequences of 30 trades each. It means
that if you take 30 trades for 1,000 times, the maximum
drawdown shown is not exceeded for 950 times.
Is that good enough for you?
You have to decide by considering your hunger for profits and
your need to avoid risk of ruin. By demanding a lower certainty
for the maximum drawdown figure, you will be able to trade
larger sizes which would theoretically lead to more profits.
However, the lower certainty also means that you face a higher
risk of ruin due to possible underestimation of the maximum
drawdown figure.
I use 99% for estimating maximum drawdown. I prefer to stay
conservative for this measure as it affects the likelihood of my
account being ruined. I like to continue trading more than I like
pushing my profits to its theoretical maximum. I am satisfied
knowing that as long as my account is not ruined over the long
run, I will be profitable.
The point of trying to find out our maximum drawdown is to
decide on our position size. With the maximum drawdown and
our account ruin point, we are able to do so.
For trading one contract, we need:
Account Ruin Point + (Maximum Drawdown x Safety Multiple)
= $1,005 + ($9009 x 2)
= $2,805
9
Simulated the same sample strategy for 1,000 sets of 30 trades
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The safety multiple is another feature to deal with uncertainty. A
low multiple is aggressive (minimum 1) and a high multiple is
conservative. I use a default of 2.
For a $10,000 trading account, the position size is:
$10,000 / $2,805 = 3 (rounded down from 3.56)
Our Monte Carlo tool calculates the position size for you
automatically using the maximum drawdown from your
simulation results. Just enter your account size, ruin point, and
safety multiple and it will compute the position size for you.
Figure 6-8 shows a snapshot of the position sizing tool included
with the Monte Carlo Simulator.
Figure 6-8 Position sizing tool linked to Monte Carlo drawdown results
Bear in mind that our calculation assumes that the minimum
trade size of your trading strategy is one contract.
This position sizing model is easy to understand and can be
tweaked according to your risk appetite. It is simply based on
the objective of avoiding the risk of ruining your trading
account.
There are many other position sizing models ranging from a
simple 2% risk rule to the more sophisticated Kelly criterion
derived from probability theory and inter-temporal portfolio
choice. If you are keen to explore other position sizing models,
refer the resource page.
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Regardless of which position sizing model you employ, there is
an important first principle. If the expectancy of your trading
strategy is not positive, your trade size should be zero.
FIRST PRINCIPLE
Do not trade if your trading strategy
does not have an assessed positive
expectancy
6.4.4 - Improving Expectancy
We must trade with a strategy of positive expectancy. If our
expectancy is negative, we ought to improve it until it becomes
positive. Even if we are confident that we have a trading edge,
we still have great incentives to improve it or at least monitor it
for deterioration. This is the topic we are dealing with here.
Our general approach is to classify/tag trades according to
certain characteristics and analyse them to draw useful
conclusions.
Reviewing Trading Performance
To start tweaking our trading process, we must first find out
what is working and what is not. We need to answer these
questions
1. Are our trading rules and guidelines sound?
2. Is our discretion adding value to our trading
performance?
3. Are we disciplined?
Recall the trade classification we performed earlier - Consistent,
Discretionary, and Rogue. We are unlocking its value here to
help us answer these questions.
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Are your trading rules and guidelines sound?
1. Filter your Trade Records to show only the Consistent
trades.
2. Measure the expectancy of your Consistent trades,
according to the steps described earlier.
A positive expectancy reflects the soundness of your trading
rules and guidelines. It means that total compliance with your
rules and guidelines contributed to your trading edge.
If the expectancy is negative, it is likely that you need to tweak
the rules and guidelines. To find out what tweaks are necessary:
1. Focus on the Consistent trades.
2. Retrieve the Analysis Matrices that supported these
trades.
3. Look at their charts.
4. Aim to find the difference in price action between the
winning and losing trades. What is common to the
winning trades and is generally not found in the losing
trades? What is common to the losing trades and is
generally not seen in the winning trades?
Even if the expectancy of your Consistent trades is positive, you
can still adopt the same process to further improve your trading
performance.
For instance, you might find out that long trades tend to fail if
they take place right after three consecutive bearish bars.
Similarly, short trades tend to get stopped out when they occur
right after three consecutive bullish bars. At the same time, you
find that none of the winning trades showed this specific price
action feature. In that case, you should consider adding a
trading rule/guideline that forbids such trades.
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However, it is important not to fall into the trap of the Holy
Grail. In your review of the losing trades, you might be tempted
to find something that can eliminate all losing trades. That is the
lure of the Holy Grail. Do not fall for it.
To avoid the trap, be reasonable and always ponder on the
consistency of any new trading rule/guideline or any
modifications to them. For instance, the “three consecutive
bars” example above seems to suggest that we should not act
against market momentum. Such a rule is consistent with our
understanding of price action.
You might find that if you take a small profit of 2 ticks each
time, you can avoid all losing trades in the sample. Should you
then add a trading rule to take a 2-tick profit for every trade?
You should not because this trading rule is unreasonable and
inconsistent. It is unreasonable because eliminating all losing
trades is not our aim and is often a clear sign that we are
seeking the Holy Grail. It is inconsistent because we know that
taking small profits of 2 ticks will almost definitely push most
trades into negative expectancy. Furthermore, our
understanding of price action clearly tells us that we should
target using price action features or market volatility. Both
factors are dynamic. Using a fixed tick target is contrary to our
understanding.
Is your discretion adding value to your trading
performance?
1. Filter your Trade Records to show only the Discretionary
trades.
2. Measure the expectancy of the Discretionary trades,
according to the steps described earlier.
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If the resulting expectancy is positive, you are proving your
competence as a discretionary trader. With the help of your
Analysis Matrices, recall your thought process and feelings
during each trade. Then, attempt to positively reinforce them in
your future trading decisions.
On the other hand, if your Discretionary trades show negative
expectancy, you should reduce the discretion you take and stick
to your trading guidelines. This is especially so if your
Consistent trades exhibit solid positive expectancy.
Being able to review Discretionary trades is a huge advantage;
it allows you to know if your discretion is adding value to your
trading. Most discretionary traders work under a pure trust of
their trading gut. It does not have to be that way. For novice
traders, being able to monitor the progress of your discretionary
trading skills is helpful and reassuring.
Are you disciplined?
1. Filter your Trade Records to show only the Rogue trades.
2. Measure the expectancy of the Rogue trades, according to
the steps described earlier.
This is straightforward. The mere fact that you have Rogue
trades in your Trade Records means that you are not entirely
disciplined.
Most traders do not have a system to keep track of Rouge
trades and are unable to quantify the losses brought about by
these bad trades. With records of Rogue trades, we are able to
quantify the cost of not being disciplined and giving in to
emotions.
Having an actual loss figure attributed to a lack of discipline and
mental resilience makes it a lot harder to deny that you have a
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problem with your psychology. It also provides concrete
incentives to improve your discipline.
“If I had been disciplined, the balance of my trading account
would be $X higher.”
Everyone says that psychology is important to trading
performance and stops at that. With records of your own Rogue
trades, trading psychology is no longer a vague concept. It has
a dollar amount attached to it.
What if our Rogue trades show a net profit or even positive
expectancy? Does that mean that you should continue to ignore
your trading rules and guidelines?
No. This is because you cannot replicate your performance with
Rogue trades. Rogue trades, by definition, defy your trading
rules and guidelines. You cannot reproduce them with your
trading rules. You cannot even write down any trading rules that
might reproduce them. The real underlying problem with Rogue
trades is not the losses they bring, but the inherent
inconsistency. Thus, even if your sample of Rogue trades shows
a net profit, you should not rejoice as it means nothing beyond
transient good luck.
As I have mentioned, we all tend to judge the validity of our
actions (trades) by their outcomes (net profit). Hence, when
faced with a set of profitable Rogue trades, it is unsurprising
that some traders start to argue that it is their subconscious
trading talent at work. They say that they are good
discretionary traders, although they are not sure how to
articulate their reasons behind each trade.
This is why we must insist on ex-ante trade classification. Based
on our ongoing written analyses, we classify a trade the
moment we decide to take it and before we know its outcome.
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Ex-ante classification of trades is far more objective than expost claiming of credit on the basis of some unknown X factor.
On this note, let me expand on the topic of what makes a
discretionary trade. I agree that it is not always possible to
explain the reasons behind a discretionary trade.
Generally, rules must be complied with. Guidelines, if broken,
must be justified. What if you cannot justify the violation of a
guideline in words? All you know is that you have this nudging
feeling that this trade is likely to succeed. In that case, ask
yourself if you are taking this trade out of fear, greed, or
boredom. If you are not affected by any of these undesirable
feelings, then mark the trade as “Discretionary”. It boils down to
how truthful you are with yourself.
Regardless of how you differentiate between a Discretionary
trade and a Rogue trade, always remember to classify your
trades ex-ante. This practice is important for you to distinguish
between luck and skill.
The difference between luck and skill is simple. If I am skilful at
singing, I can say “Listen to me. I am going to sing in tune.”
And then I proceed to sing in tune, most of the time. (In this
respect, being tone deaf, I am not at all skilful.)
This is how we prove that we are skilled at doing something.
The point is that being able to perform what we set out to do
consistently is a mark of skill and not luck. It means we know
what we are doing.
The unacceptable approach is this. I simply sing without saying
anything. If I happen to sing in tune, I claim credit. If I go out
of tune, I start trying to explain that it was an isolated incident
because I was distracted by the bird flying past the window.
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This is why we need to commit to classifying our trades ex-ante
instead of pushing blame or taking credit only after our trades
conclude.
Similarly, in trading, a skilled trader should be able to say “Look
at this trade I am going to take. It is a trade with positive
expectancy.” And then, the skilled trader proceeds to take the
said trade.
Pay attention to what the trader said: “Trade with positive
expectancy” and not “winning trade”.
Hence, each individual trade need not be profitable. The
expectation is that a large sample of such trades should be
profitable.
Consider a large sample of trades that exhibit positive
expectancy according to our Monte Carlo simulation. For each
trade within the sample, the trader has classified them as
Consistent, Discretionary, or Rogue ex-ante. Under such
circumstances, it is undisputable that the trader is skilled.
Again, this section highlights the relationship among the
different stages of the Analytical Cycle. It is important that we
perform the trading, recording, and classifying seriously to
enable a proper review of our trading performance.
In conclusion, there are three ways to improve our trading
performance.
1. Improve our objective criteria for taking trades
2. Improve our trading gut (discretion)
3. Improve our discipline and mental resilience
All three ways are challenging.
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However, improving our discipline and mastering our emotions
produces the most certain and greatest improvement in trading
performance. In fact, if you are not disciplined enough to follow
your rules and ignore your destructive emotions, no amount of
improvement in your trading rules and skills would matter. We
will discuss more about the psychology of trading in the next
chapter.
Drilling for Specifics
Reviewing our trades according to the classification of
Consistent, Discretionary, and Rogue is helpful. We are able to
find out the strengths and weaknesses of our trading rules,
trading skills, and mental state.
However, if we want specific and practical ways to improve our
performance, we need to expand the review with finer
classifications. Essentially, we go beyond Consistent,
Discretionary, and Rogue. We classify our trades according to
their characteristics. The objective is to analyse how different
trade characteristics contribute to our trading performance.
There are many ways to tag your trades. You can use any
attribute of a trade as long as you can reliably determine it.
The process is akin to an experiment. First, we form a
hypothesis about a factor that might be affecting our trading
performance. Then, we identify trades with that factor and
group them together. Finally, we examine if our hypothesis is
correct.
For instance, I notice that the price action on Fridays is usually
dull and there are not many opportunities for profit. As a result,
my trading style does not perform well on Fridays.
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To confirm this, I identify all my Friday trades and compare their
overall performance with trades from other weekdays. If I find
that, indeed, my Friday trades on a whole are barely breaking
even, while my trades on other days are making most of the
profits, I should consider resting on Friday. Alternatively, I could
also attempt to tweak my trading strategy on Fridays.
Day of the week is an example of an objective segment. Other
examples include:




Time of the day (first two hours, last two hours)
Market (CL, ES, FDAX)
Time frame (5-minute, 30-minute, 1-hour)
Setups (Deceleration, Trend Bar Failure, Anti-Climax)
For day traders, when we trade is almost as important as how
we trade. It is not because Lady Luck smiles more at certain
hours of the day. It is because market volatility varies
throughout a trading session. For most markets, the first two
hours of the session are the most volatile. As a result, many
traders find that most of their profitable trades are concentrated
in the earlier part of the trading session. In that case, they
might do better by restricting their trading to the first two hours
of each session.
Of course, this might not apply to you, given your traded
market and trading style. However, if you have kept good
trading records, it should not take too much to find out if certain
hours are superior for trading. Simply filter your Trade Records
to show only trades within the first two hours of each session
and examine their performance as a whole.
Many traders look for different setups in multiple markets and
various time frames before eventually specialising in a couple of
them. This is because the price action (including speed and
volatility) of each market differs. A trader’s preference depends
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on his or her temperament and trading style which will take
time to develop.
We have already recorded the basic trade information in the
Trade Records worksheet. Hence, you can easily filter the trades
accordingly.
For instance, you can filter to show only trades in the Crude Oil
market. Then, compare it to the trades in the S&P E-mini
market. If you find that you are consistently making money
from Crude Oil and not so in S&P E-mini, you might consider
focusing on the Crude Oil market. You can experiment with
different filters using other parameters like time of the day and
type of setups.
There are also less objective, but equally useful segments.
These segments are often based on price action features. It
usually involves questioning if our current price action analysis
is effective and paying attention to ways to improve it.
For instance, as I trade, I notice that the first trade after a
newly formed trend line has a higher probability of success than
subsequent trades. To confirm this observation, I manually tag
the first trade after the formation of a new trend line. After
tagging a number of trades, I am able to review their
performance and assess my hypothesis. If it turns out that the
first trade following a new trend line has a higher expectancy, I
can focus on finding such trades or consider increasing my
position size for these trades.
There are infinite possibilities. This is why our Trade Records
has additional columns from “Custom 1” to “Custom 10”. You
can replace the headings and use these columns to help you tag
trades according to their price action features.
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For instance, replace “Custom 1” with “First Trade after a New
Trend Line”. Then, for that column, enter “Yes” if a trade follows
right after a new trend line. Once you have collected a decent
sample of trades with “Yes”, filter your Trade Records to see if
they are indeed superior trading opportunities in terms of
expectancy.
This is a systematic approach to catalogue your price action
observations and develop your trading instinct.
Other than tagging trades based on their characteristics, there
is another productive use of these “Custom” columns. We can
use them to consider the impact of virtual decisions.
What are virtual decisions?
Virtual decisions are alternative trading actions that you would
like to track and examine.
For instance, in a long position, you exited with a target order at
the nearest resistance with a small profit. At the same time, you
wondered if it was better to let your profits run by trailing a
stop-loss order below each new swing low. To find out, you can
make a virtual decision.
Virtual decisions are the what-if scenarios.
What if I place the stop-loss order below the entire price pattern
and not just below the setup bar?
What if I exit a trade if it does not show positive momentum
within five bars?
What if I wait for the high of the session to be cleared before
taking a long position?
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What we really want to find out is if taking these alternative
(virtual) decisions would produce better trading results. Does
the alternative lead to a better or worse trade outcome?
Considering these what-if scenarios is a natural progression for
any trader seeking to improve his or her performance. In fact, it
is an important endeavour and a means to achieving better
results, especially for more experienced traders.
To find the answer, each time you see an opportunity to
consider an alternative action, record it as a virtual decision and
note its outcome.
For instance, at some point after you enter a trade, you are
thinking about moving your stop-loss order to breakeven.
However, your rules do not allow you to do so. Being a
disciplined trader, you stick to your rules. However, you can
record a virtual decision of shifting your stop-loss to breakeven.
To do so, replace one of the “Custom” headings with “Breakeven
Stop-Loss”. Then, in the row belonging to the trade you are
recording, enter the net profit/loss of taking that alternative
action, which is placing a breakeven stop in this case.
Let’s say for the actual trade, you exited with a 20-tick profit
without adjusting your stop-loss to breakeven. And if you had
shifted the stop-loss to breakeven when you thought of doing it,
you would have exited the trade at breakeven due to whipsaws.
In this case, you would record 20-ticks as your actual profit and
0 tick as your virtual profit resulting from the virtual decision.
After a series of trades implementing the same virtual decision,
you will get a sense of whether the alternative action is superior
to your current rules and guidelines.
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The best part of making virtual decisions is that you can stick to
your trading rules while exploring new possibilities in your
trading method. You do not influence your live trading with
premature conclusions. At the same time, you do not give up
any chance of gaining new price action insights.
However, don’t go crazy with implementing virtual decisions.
There are infinite what-ifs in trading. It is impractical to keep
tabs on too many alternate decisions. Based on your trading
experience, choose several promising alternatives and monitor
them.
Essentially, our approach to improving the expectancy of our
trades revolves around classifying/tagging our trades to
segment them for review. Table 6-3 shows the tags and their
respective functions.
Tag
Consistent
Discretionary
Rogue
Objective Characteristics
(using standard columns)
Subjective Characteristics
(using custom columns)
Virtual Decisions
(using custom columns)
Function
Monitor the soundness of trading
rules and guidelines.
Monitor the development of
discretionary trading skills.
Quantify losses due to
psychological issues.
Refine trading period, time frame,
market, etc.
Refine price action interpretation.
Test alternative course of action.
Table 6-3 Tags and their functions
Before we end this section, I would like to warn you against
vanity metrics. Armed with a large set of Trade Records, you will
be able to slice and dice them in numerous ways and calculate
various metrics.
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Regardless of what you do with the data, do not waste your
time calculating metrics that are not actionable.
For instance, the Sharpe ratio is a popular risk-adjusted
performance measure among portfolio managers. Some traders
calculate this ratio as well. The question is: what do you do with
it? How does it lead to an improvement of your trading
performance?
I do not calculate the Sharpe ratio as I do not know what to do
with that number.
Do not calculate numbers and run simulations for the sake of
doing so. The objective of a trade review is to arrive at practical
steps to improve our trading.
This also explains why we use a tagging approach in our review.
We tag trades according to certain characteristics and review
them. If the tagged trades are superior, we can improve our
trading by looking out for those characteristics. If they are
inferior, we can improve by avoiding those characteristics. In
any case, we are always able to link our review process to
practical actions to help us improve our trading.
TASKS – STAGE FOUR
1. Measure your expectancy using Monte
Carlo simulation
2. Derive your position size using the
maximum drawdown method
3. Tag your trades and review them for
areas of improvement
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6.5 - Refine Trading Rules and Guidelines
It’s time to complete our Analytical Cycle. The key purpose of
going through the prior stages is to improve our trading
premise, before we start all over again. Based on what we
gather in Stage Four, we can refine our trading rules and
guidelines.
There are two pertinent points to note for refining trading rules
and guidelines.
First, do not change your trading rules based on a small sample.
Accumulate more trade records before concluding if the
intended change in a trading rule or guideline is beneficial. Your
actual trades might not offer a sufficient sample size.
In that case, record trades that you missed as well, either
because you were away from your trading desk or did not trade
the session. I am referring to trades that you would have taken
according to your trading rules if you had the chance. These
trades should be tagged as “Virtual Trades” using one of the
custom columns. Use them only for assessing possible
improvements. Do not include them for measuring your trading
expectancy or maximum drawdown as they were not taken in
real-time.
When you are unsure if you should alter a trading rule or
guideline, don’t hesitate to use a virtual decision to gather more
information before deciding.
Next, avoid drastic changes. “Refine” means making minor
improvements. Drastic and frequent changes to your trading
rules and guidelines make it difficult to review your trading
performance.
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Trading rules and guidelines form the basis for every trade you
take. They ensure the common ground for trade review and
improvement. Drastic and frequent changes destroy the
common ground and render your trade review ineffective. If the
basis of your trades changes from trade to trade, there will be
hardly any ground for comparison.
6.6 - Conclusion
The Analytical Cycle sounds like a chore. However, I assure you
that it is a solid framework that will work regardless of your
traded market, time frame, or strategy. As you work your way
through the cycle repeatedly, you will gain confidence in your
trading skills and eventually develop your own trading style.
Do you want to create your own trading success without relying
on trading gurus?
Do you want to continue trading profitably in a changing
market?
Do you want to get out of a state of denial and speculation when
it comes to trading?
If you answered yes to the above questions, you must employ
the Analytical Cycle. It is based on common sense and designed
to mitigate cognitive biases. It is simple and straightforward.
And being a generic approach, it works for all trading styles and
is yet independent from any trading style.
On top of that, your Toolkit has everything you need to embark
on this rigorous tracking of your trading activities. You just need
to enter your trade information into the Trade Records
worksheet.
Start today!
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Chapter 7 - A Risk-Based Approach
to Trading
In many ways, “trader” is a misnomer for describing people like
us. We should be called risk managers. “Trader” describes what
we do when we click the buy and sell buttons. However, what
are we really doing by pressing the buttons? We are assuming
and managing trade risks. The game is about finding risks that
are worth taking. Hence, “risk manager” more accurately
describes what we do constantly.
At the core of our trading process, we are basically taking on
risks. With each trading opportunity, we are assessing if the
trade risk is worth taking. The main idea is to take on risk that
promises net positive returns over the long run. We evaluate the
risk and take them on with the intention of making money.
Assuming the right trade risks is what gives us our trading edge.
Finding desirable trade risks has been our focus so far. Indeed,
that is the main role of a trader. However, traders face many
risks beyond the amount we stand to lose for each trade.
With an in-depth examination of the risks associated with
trading, you will realise that being a trader is much more than
being an analyst and extends very much beyond the market.
To complete your trading plan, you need to look beyond trade
risks.
You will realise that, in a nutshell, focusing on risks is the best
way for a trader to put everything together.
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7.1 - Identifying Risks
Risks do not occur in a vacuum. Risks are defined in relation to
our environment, resources, and most importantly, our
objectives. Hence, our first step is to refocus on our objective.
Objective: To earn a profit by taking trades of positive
expectancy.
With respect to this objective, let’s separate a trader’s risks into
intrinsic risks and external risks.
INTRINSIC RISK
We do not know how to find trades that
offer positive expectancy
Intrinsic risk relates directly to our objective. It is the
essential/pre-requisite skill of any endeavour. In this case, it is
the skill of looking for trades of positive expectancy. It
represents the risk of not being able to find trades that offer
positive expectancy. If you do not know how to analyse the
market to find trades of positive expectancy, you cannot
succeed as a trader.
You can buy a super computer, pay zero commissions, lease a
CME membership, and start with 1 million dollars. You will still
fail. This is because you have not addressed the intrinsic risk of
your objective. This is the type of risk we have been focusing on
so far.
The way to manage this risk is to learn how to read the market
to find opportunities of positive expectancy. We have learned
how to read price action and pinpoint specific trading setups
that offer positive expectancy. The previous chapter completed
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our treatment of the intrinsic risk with techniques to assess and
improve our trading edge.
Employ the price action trading techniques you’ve learnt and
trade in simulation mode to build up your trading record. Then,
use the Monte Carlo simulation tool to assess if your records
exhibit positive expectancy. These steps will ensure that you
have the skills to pick out trades with positive expectancy.
Essentially, these steps help to control your intrinsic risk.
Assuming that we know how to find trades with positive
expectancy, does that mean that we will become profitable
traders?
No, because there are external risks that we need to address.
EXTERNAL RISK
We know how to find trades that offer
positive expectancy, but we are unable
to take them
External risks do not give us our trading edge. However, they
can easily destroy our trading edge if they are not managed
well.
Traders commonly blow up their trading account because they
mismanage or neglect these risks, even though their trading
strategy is sound. If such risks are not controlled, they can
easily wipe out your trading edge.
These risks stem from the fact that being able to find good
trades will not make us a single cent. I can note down every
single trading opportunity with positive expectancy in my
notebook, sit there, and stare at the screen. Even if these
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trading setups turn out to be profitable, I would not have made
a single cent.
Why? Because I have not placed any order to be executed in the
market. I have not traded. Without actually trading, regardless
of how fantastic my market analysis is, I cannot make a living.
To achieve our objective of making money, we must actually
trade based on our analysis.
To start making your first dollar from the market, you need to
actually execute a trade.
Let’s look at an analogy. You aim to become a successful author
by publishing a great novel. You have dealt with your intrinsic
risk, that is, you have acquired the writing skills and exercised
your creativity to finish a great novel. However, does that mean
that you will become a successful published author?
No. You face the risk of losing your only manuscript when your
computer fails. You face the risk of not having the confidence to
pitch your book to literary agents. You face the risk of being
rejected by the big publishing houses. If you intend to selfpublish, you face the risk of not having enough cash flow.
There are many risks. These risks are external to your great
creative work. The truth is that a writer has to worry about
more than just writing a great book. Similarly, a trader has to
worry about more than just finding great trades.
Finding good trades is necessary but not sufficient for trading
successfully. We must be able to commit to these trades
financially in order to attain our objectives. There are many
risks and obstacles that might stand in our way.
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The identification of external risks is a structured yet creative
process. We need to go through each step of our trading
process methodically and yet actively imagine what could
possibly go wrong. It should be a painstaking first step.
Fortunately, we have many fellow traders to learn from. A
simple literature review and my personal trading experience
reveal that the risk to our ability to trade according to our
analysis revolves around three aspects.
Remember that in addressing external risks, we are assuming
that our analysis is solid. We should follow what our price action
analysis dictates. However, due to one or more of the reasons
below, we might be unable to do so.
1. When we run out of money, we cannot trade according to
our analysis. (Financial risk)
2. When our trading infrastructure/environment is not
working, we cannot trade according to our analysis.
(Operational risk)
3. When our minds are hijacked by our emotions, we cannot
trade according to our analysis. (Psychological risk)
Each of the reason above corresponds to a type of risk that
requires our attention.
We have already dealt with intrinsic risk. Hence, this chapter will
focus on external risks. The integration of the different risks will
complete our trading perspective and, more practically, our
trading plan.
In the following sections, we will take a closer look at specific
risks. For each of them, we will complete a Risk Management
Card, a simple tool to help us to work our way from risk
awareness to practical ways of managing risk.
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Risks are highly dependent on the circumstances of each
individual trader. Hence, I cannot and will not provide an
exhaustive list of risks. We will focus on the major risks and the
common means to deal with them. The real aim of this chapter
is to increase your risk awareness and to use the Risk
Management Card to manage individual risks.
7.2 - Risk Management Card
To ensure that our discussion concludes with actionable steps to
manage each type of risk, we adopt an established risk
management process.
1. Identify risks
2. Analyse risks
3. Prioritise risks
4. Treat risks
5. Supervise risks
This framework is derived from the “Overview of Enterprise Risk
Management” issued by the Casualty Actuarial Society. It is also
included in the curriculum of the Financial Risk Manager (FRM)
qualification. It is designed with an enterprise in mind. The
resources available to an enterprise are beyond that of any one
trader. Luckily, the risks that a trader faces are also more
limited in scope.
The Risk Management Card represents a practical application of
this robust framework for the individual trader to manage his
risks.
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Table 7-1 explains the parts of a Risk Management Card.
Risk
Identify
Function
State and describe the risk.
For every step in your trading process, ask “What
could go wrong?”
Analyse
Explain the factors that affect the probability and
magnitude of this risk. Apply simulation techniques
and scenario analysis.
Focus on their impact and likelihood of taking
place. Seek to understand the true nature and
implications of each risk.
Prioritise
Examine the impact of leaving this risk unmanaged
and prioritise it. This will affect the amount of time
and resources we devote to managing this risk.
Treat
For each assessed risk, we should try to:





Eliminate it;
Reduce it to an acceptable level;
Transfer it;
Accept it; or
Exploit it.
Our analysis above would have revealed the
potential impact of leaving the risk unmanaged
and the likely costs of containing it.
To decide on our course of action, we need to
review our resources and environment to
understand how they advance or hinder our path
to our goal of taking trades with positive
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Risk
Function
expectancy.
State how we intend to avoid, reduce, or transfer
the risk. Depending on the circumstances, we can
also accept or exploit the risk.
Focus on action items.
Remember that you can always choose to accept a
risk if the probability of a loss is low compared to
the cost of mitigating it. This is the essence of a
risk-based approach. We are not trying to create a
zero-risk environment. We are aiming for an
awareness of risk factors in our trading process
and environment, and to treat them sensibly,
given our resources.
The courses of action listed in the Risk
Management Cards that follow are general
recommendations. Adapt them for your personal
circumstances.
Supervise Risks evolve.
List down relevant risk items to monitor. (E.g.
drawdown or financial soundness of broker etc.)
Table 7-1 Risk Management Card
In the following sections, we will assume the perspective of a
futures trader who intends to day trade using price action. From
this standpoint, we apply the Risk Management Card on specific
risks.
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7.3 - Financial Risk
Let’s break down the main financial risks of a trader. (We are
not talking about trade risk here.)
1. Risk of not having enough trading capital
2. Risk of not having enough living expenses
3. Currency risk
7.3.1 - Trading Capital
We have discussed the risk of drawdown in trading strategies in
the previous chapter. Here, the Risk Management Card provides
a structure to our thought process.
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Risk
Function
Identify
Every trading strategy encounters drawdowns.
Hence, we face the risk of not having enough
trading capital for the strategy.
Analyse
How much trading capital is enough?
We have already gone through the drawdown
analysis in the last chapter. The maximum
drawdown figure from the Monte Carlo simulation
is a good starting point.
Prioritise
The impact of having insufficient trading capital is
severe. It will render us unable to trade.
This is top priority.
Treat
1. Use drawdown analysis to calculate the
amount we need to trade the minimum size.
2. Save enough trading capital to start trading.
3. Implement position sizing model according
to the maximum drawdown approach. For
details, refer to Chapter 6.4.3 - Computing
Drawdown (for Position Sizing).
Supervise
1. Review the maximum drawdown figure
regularly using a larger trade sample for
simulation analysis.
2. Adjust the position sizing model inputs
accordingly.
Table 7-2 Risk of not having enough trading capital
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7.3.2 - Living Expenses
A trader’s risks often extend beyond the market and the trading
strategy. If you intend to day trade for a living, you need to pay
attention to the risk of not earning enough.
Even for a profitable trader, the cash flow from your trading
income will be largely irregular, unlike a salary from a normal
job. Thus, traders need to watch their personal finances closely.
Risk
Function
Identify
Trading produces volatile income (if any). Hence,
traders face the risk of not being able to meet their
living expenses.
Analyse
How much living expenses do you need?
Keep records of your expenditure over a few
months to estimate your average monthly
spending.
Do you trade full-time or part-time?
If you intend to rely on trading for your sole source
of income, the volatile nature of trading represents
a major risk.
If you intend to day trade part-time, your income
from your day job should be able to meet your
living needs. The risk of not having sufficient living
expenses while you trade is reduced.
Prioritise
Treat
Without income for basic survival, we are unable to
trade. Hence, this risk is top priority.
1. Avoid this risk by securing another source of
income to meet your living expenses.
2. If you intend to trade for a living, save at
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Risk
Function
least 1 year worth of living expenses before
you start day trading. That sum does not
include your trading capital.
3. If you plan to trade part-time, lower the
savings amount accordingly.
Supervise
1. Monitor your living expenses to ensure that
it is within your projection.
2. If your trading proves profitable, consider
setting up a system for withdrawing profits
to cover expenditure.
Table 7-3 Risk of trading income not meeting living expenses
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7.3.3 - Currency Risk
The currency risk discussed below shows how risks depend on
the circumstances of individual traders.
Day traders are generally not exposed to significant currency
risks due to their short holding periods. However, currency
fluctuation might pose a problem if the currency of your trading
account is different from your home currency (i.e. the currency
you intend to spend in).
For instance, you trade the US markets using a USDdenominated trading account. However, you stay in Thailand
and expect to withdraw your earnings in Thailand Baht (THB).
The value of your profits to you is affected by the strength of
USD versus THB. If USD appreciates, you stand to gain. If USD
depreciates, your USD trading profits convert to less THB.
Risk
Function
Identify
The value of your trading account balance is
subject to currency risk due to the difference
between the currency base of your trading account
and your home currency.
Analyse
How much do you intend to keep in your trading
account?
The larger the amount in your trading account, the
larger the currency risk.
What is your view on the volatility of the relevant
exchange rate?
It depends on the historical volatility of the
currency pair and your take on its future volatility.
The larger the volatility, the greater the risk.
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Risk
Function
Prioritise
The priority of this risk depends on the currency
pair involved and the size of your trading account.
However, while currency changes might affect the
value of our trading account, it is unlikely to have
a catastrophic impact on our trading activities.
Generally, this risk is of medium priority.
Treat
1. Avoid this risk by using a trading account
denominated in your home currency.
(subject to the availability of brokerage
account options and trading markets)
2. Reduce this risk by keeping just enough
money in your trading account to trade your
trading strategy.
3. Transfer the risk using hedging techniques.
(spot forex/currency futures)
4. Accept the risk if the size of your trading
account is relatively small.
5. Exploit the risk if you think that the currency
change will be in your favour. You can do
this by timing your withdrawals. However,
this is equivalent to taking a separate forex
trade. Proceed with caution.
Supervise
1. Monitor currency changes and account
balance.
2. Review brokerage account options. For
instance, your broker might start to offer a
trading account denominated in your home
currency.
Table 7-4 Currency risks of international trading
The above risks represent some of the major financial risks that
might impede your trading. If you become aware of additional
financial risks, use the Risk Management Card to assess them
like we did above.
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7.4 - Operational Risk
Within the context of an individual day trader, operational risk
refers to the risk associated with the actual trading process - the
actual action of clicking the mouse button to place a trade.
Trading process here refers to the actual placing of orders to
trade and not the process of analysis.
Placing a trade may seem like just a mouse-click. However, it is
clear that we need a great deal more than just a computer
mouse to place a trade. To place a trade in the market, we need
the following:







Computer with keyboard and mouse
Electricity
Internet connection
Brokerage account
Trading platform
Knowledge of how to use the trading platform
Working space clear of distraction
To break down the aspects of operational risk, we need to go
through each part of our trading process.
For instance:




What can go wrong with our computer?
What can go wrong with our electricity supply?
What can go wrong with our Internet connection?
And so on…
These are the type of questions we need to ask to pinpoint
specific operational risks.
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The following Risk Management Cards address the risks
associated with each aspect stated above.
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7.4.1 - Trading Computer
Risk
Function
Identify
Risk of trading computer failure
Analyse
What is the condition of your computer?
The probability of a computer breakdown is a
function of its age, workload, and quality.
However, the failure of a computer is certain. Your
trading computer will fail. The question is when.
Prioritise
If you cannot power up your computer to start
trading, simply buy a new computer. This is a lowrisk event.
However, if your computer fails or hangs during a
trade, it might bring about catastrophic
consequences. We will not be able to monitor the
trade. For a day trader, this might bring about
unexpected large losses.
This is especially so if your stop-loss and target
orders are held locally by your computer. If so,
after your computer shuts down, you have no
stop-loss and target orders working for you. Your
potential loss is unlimited.
This is top/medium priority.
Treat
1. Avoid the risk of unmanaged open positions
by looking for a broker that holds your
orders at their servers.
2. Have your broker on speed dial so that you
can close your open positions in case of
emergency.
3. Reduce the risk by taking care of your
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computer.
4. Dedicate a computer to trading. Do not use
it for any other activities.
5. Get a backup computer/laptop.
6. Backup trading records.
Supervise
1. Look for signs of failure. (E.g. increased
errors, slowdown, automatic shutdowns
etc.)
2. Replace your computer if necessary. From a
business aspect, it’s a good idea to plan the
replacement of your computer to ensure
work continuity. If you wait until your
computer fails before buying a new one,
your trading will be disrupted and data
transfer will be more tedious.
Table 7-5 Risk of computer failure
Adapt the Risk Management Card according to your specific
context. For instance, if you use a wireless computer mouse, it
will run out of power. You do not want to miss a trade because
of that. You can devise ways to treat this risk. You can prepare
spare batteries, use a wired mouse, or learn how to execute
trades with only your keyboard.
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7.4.2 - Electricity
Risk
Function
Identify
Risk of unreliable electricity supply.
Analyse
What is the probability of the electricity supply
being disrupted?
It depends on the utility infrastructure of the
country/area you intend to trade from. On top of
that, the likelihood of disasters like earthquake and
hurricanes also play a role as they might disrupt
electricity supply.
Prioritise
The consequence of a disrupted electricity supply
is similar to that of a computer failure.
This is top/medium priority.
Treat
1. Avoid the risk by using an uninterruptible
power supply.
2. Accept the risk if the probability of electricity
failure is extremely low.
Supervise
1. Monitor the reliability of your electricity
supply, especially if you have moved your
trading operations to another locality.
Table 7-6 Risk of a power disruption
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7.4.3 - Internet Connection
Risk
Function
Identify
Risk of having an unstable Internet connection.
Analyse
What is the probability of the Internet connection
being disrupted?
It depends on the communications infrastructure
of the country/area you intend to trade from. It
also depends on the reliability of your network
components like router, Ethernet cable, Wi-Fi
adapter etc.
For day trading, while the speed of your
connection is important and should be reasonably
high (at least 1mbps), the stability of your
connection is even more critical. If an Internet
connection drops off while you are trading, you
stand to lose far more than a millisecond delay in
getting your orders to the exchange.
Prioritise
The consequence of a failed Internet connection is
similar to that of a computer failure.
For all trading purposes, the computer is useless
without an Internet connection for us to download
price data and send our trading orders.
This is top/medium priority.
Treat
1. Reduce the risk of your Wi-Fi signal
dropping off by using an Ethernet cable for
wired Internet connection.
2. Get a standby Internet connection from
another provider. (Just in case the problem
is ISP-wide.) For instance, a 3G data
connection tethered from your mobile
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device.
3. Have your broker on speed dial so that you
can close your trading position without an
Internet connection.
Supervise
1. Monitor the reliability of your Internet
connection, especially if you have moved
your trading operations to another locality.
Table 7-7 Risk of disrupted Internet connection
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7.4.4 - Broker
Risk
Function
Identify
Risk of technical issues with our broker.
Analyse
What is the probability our broker experiencing
technical issues?
Our broker’s technical expertise and systems are
largely opaque to us. However, generally, most
reputable and well-regulated brokers have decent
infrastructure.
We are largely concerned with technical issues that
affect our ability to trade according to our analysis.
This refers to problems with trading platforms,
servers etc.
Other technical issues are less important to us. For
instance, problems with your broker’s
informational website.
Prioritise
Technical issues might affect the execution of our
trading orders and their accuracy. It might also
affect our connectivity to the broker’s server.
Basically, we will not be able to trade freely
according to our trading strategy if our broker is
having problems.
This is top/medium priority.
Treat
1. Familiarise yourself with alternative
channels of trading through your broker. For
instance, alternative trading platforms,
trading engines, or phone trading might be
working as usual.
2. Get a standby brokerage account that you
can use to continue trading or to hedge your
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position.
Supervise
1. Monitor the reliability and responsiveness of
your broker when they encounter technical
issues. Timely updates about technical
problems are expected.
2. Keep an eye out for reviews and news on
your broker and potential alternative
brokers.10
Table 7-8 Risk of our broker experiencing technical issues
10
A good way to do so is to set a Google Alert to monitor news on broker.
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Beyond technical issues, a broker or Futures Commission
Merchant might also experience financial issues.
Risk
Function
Identify
Risk of our broker going bankrupt or defrauding
us.
Analyse
How safe is the money in our trading account?
It depends on how well the broker is regulated and
the jurisdiction it is under. The financial numbers
of the broker, if available, will also shed light on its
financial soundness.
The segregation of client’s funds is a key concept
here. It means that the funds you and other
traders deposit with your broker must be kept
separate from the broker’s own funds. The broker
cannot use its clients’ monies under any
circumstances, even if it goes bankrupt. If there is
proper and honest segregation, your broker’s
financial soundness does not affect the monies in
your trading account.
However, in the case of financial fraud, we might
have little recourse against a bankrupt firm.
Prioritise
We risk losing our entire trading capital.
This is top priority.
Treat
1. Perform due diligence on your broker to
assess fraud risk.
2. Reduce the risk by keeping the minimum
sum you need to trade with your broker.
The bulk of your savings should not be with
your day trading broker.
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Supervise
Function
1. Monitor any news on your broker.
2. Re-perform due diligence at regular
intervals.
Table 7-9 Risk of losing our trading capital due to fraud or bankruptcy
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7.4.5 - Trading Platform
Risk
Function
Identify
Risk of our trading platform failing.
Analyse
How reliable is our trading platform?
Most trading platforms are reliable as long as their
minimum requirements are met.
When trading platforms fail to function, it is often a
problem with the backend of the broker. In that
case, we have already addressed the risk in Table
7-8.
Prioritise
Possible technical issues might affect the execution
of our orders and their accuracy. It might also
affect our connectivity to the broker’s server.
Basically, we will not be able to trade freely
according to our trading strategy if our trading
platform malfunctions.
This is top/medium priority.
Treat
1. Reduce the risk by ensuring that your
computer exceeds the minimum
requirements of your trading platform.
2. Prepare alternative trading platforms if
available.
Supervise
1. Update your trading software in a timely
manner.
2. Monitor if new versions of the software have
different requirements and update your
trading computer accordingly.
Table 7-10 Risk of trading platform failure
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7.4.6 - Execution Process
Risk
Function
Identify
Risk of making mistakes in trade execution due to
the lack of knowledge or focus.
Analyse
How familiar are you with operating the trading
platform?
The more familiar you are with the trading
platform, the less prone you are to mistakes in
trade execution.
What is your physical and mental condition?
You need to feel physically well and mentally
focused. The probability of negligence increases
with your level of fatigue.
Prioritise
Clicking sell when you intend to buy or entering a
larger position size than you intended are stupid
mistakes with potentially huge costs. If you are not
alert enough to use the platform correctly, you
should not be trading.
This is top priority.
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Treat
1. Trade in simulation mode to familiarise
yourself with the trading platform.
2. Whenever possible, use the trading platform
to minimise errors. For instance, set the
default trading size to your regular trading
size. Setup a pair of target limit order and a
stop-loss order to be placed automatically
with each new trade entry. Essentially, you
are transferring your execution risk to your
trading platform.
3. Conduct a self-check on your physical and
mental well-being before starting a trading
session. Avoid trading when you feel unwell.
Supervise
1. Check for changes in new versions of your
trading platform and familiarise yourself
with any changes.
Table 7-11 Execution risk (Self)
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7.4.7 - Trading Environment
Risk
Function
Identify
Risk of making mistakes in trade execution due to
external distractions.
Analyse
How vulnerable are you to external distractions?
Examine your trading environment. A locked,
sound-proof room is conducive for trading without
distractions. A common room where kids roam
around is less ideal.
Prioritise
We risk executing our trades wrongly or missing
good trading opportunities.
This is top/medium priority.
Treat
1. Ensure a quiet trading environment
conducive for intense focus.
2. Communicate with your family/housemates
and let them know that you should be left
alone during your trading hours.
3. Turn off your mobile and other
communication devices.
Supervise
1. Monitor changes to your trading
environment and take steps to mitigate any
new risk that arises.
Table 7-12 Execution risk due to external distractions
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7.4.8 - Minimise Risk by Keeping It Simple
We started our operational risk analysis by stating the required
items for trading. Then, we examined what could go wrong with
each item.
It follows that the more items we need for trading, the more
room for things to go wrong. This means that a complicated
trading process entails more risks. Thus, the best way to
minimise risk is to keep things simple.
Imagine a trader who has two trading computers running three
trading platforms from the four different brokers he’s using to
trade five markets with the six different trading approaches he
picked up from the seven mentors he found online. Even if we
disregard the eight trading screens he has in front of him, can
you imagine the multitude of things that could go wrong?
I am not referring to the trader who has one computer for
trading and one for backup. I am referring to the trader who, for
some reason, requires both computers to trade. If he plans for
backup computers, he would need four trading machines.
Instead of one computer that will fail, you have two. With three
trading platforms, it is harder to become proficient in using
them. Execution risks increase. Basically, having more
components in your trading process complicates your risk
context and increases the challenge of managing risks
effectively.
The best policy is to keep things simple. Start with a minimalist
mind-set. Use one computer with one screen. Stick with one
trading platform and broker. Employ one trading method in a
single market. Seriously consider the marginal value of any
addition to your trading process.
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Does it help you move closer to your objective of taking positive
expectancy trades?
If it does not, do not add it to your arsenal.
If it does, then consider its costs and risks. Is it worth it?
“Simplicity is the ultimate sophistication.”
Leonardo Da Vinci
7.5 - Psychological Risk
You have learned how to analyse the market and how to trade.
Over time, you will hone your trading skills further. In other
words, with enough effort and in a matter of time, you will know
exactly what to do in real-time trading.
The problem is, however, at times we deviate from what we
know we should do. This deviation is commonly described as a
lack of discipline that stems from our cognitive biases and
emotional flares – psychological risk.
Psychological risk is the greatest challenge to a trader’s
consistent profitability. Challenged by our emotions, we risk
ignoring the trading rules we designed to protect ourselves.
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Identify
Risk of not following our trading rules due to the
lack of discipline and control over our emotions.
Analyse
How well do you appreciate the probabilistic nature
of the market?
How scared are you of losing your trading capital?
How confident are you in your trading plan?
Ultimately, we are humans. Psychological risk is a
constant.
Prioritise
If we do not trade according to our trading plan,
we have no consistent trading edge. If we do not
follow our risk management rules like the position
sizing model, we face a high probability of ruining
our trading account.
Managing our psychological risk is top priority.
Treat
1. Understand the probabilistic nature of the
market.
2. Plan your trades meticulously.
3. Get a trading buddy/mentor to improve
accountability.
Supervise
1. Keep a trading emotion journal.
2. Review results of rogue trades.
Table 7-13 Psychological risk
Conquering our emotions and maintaining discipline is critical to
consistent trading performance. In the following sections, I will
elaborate on how to handle this risk that is embedded deep
inside our minds.
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I have briefly described several cognitive biases as I explained
our analysis process previously. Instead of repeating them with
additional academic descriptions, I will condense the
psychological risks of a trader and deal with its root cause.
Although there are numerous psychological aspects of trading, a
trader's mental challenges can be summed up with one word:
fear.
While fear and greed are often touted as the two emotions that
plague traders, we can in fact simplify our perspective and just
focus on fear.
This is because greed is profoundly related to fear.
In most cases, greed is a form of fear. Greed is the fear of
losing out or missing out. I’m scared of missing out on the next
profitable trade. This is why I am going to take this trade
although the trade risk is more than 50% of my trading capital.
Don’t ever do that.
I’m scared that I will not capture the entire price swing. So I
held on to my position although the technical signals are telling
me to exit. These are behaviours that some might describe as
greedy. I see them as forms of fear.
Greed also stems from a disrespect of fear. In fact, greedy
traders are at times fearless. They do not fear the market
because they think they are in full control or simply do not
recognise the reality of financial markets. They pay so much
attention to the potential gains from the market that they forget
about their risks. As we will discuss in-depth later, fear is useful
as long as we respond to it constructively. Fearless traders are
not good traders. Traders who respond well to fear are.
Most mental obstacles of a trader stem from fear.
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
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Traders are scared of losing
Traders are scared of losing a session
Traders are scared of a losing week
Traders are scared of a losing month
Traders are scared of missing out on good trades
Traders are scared of taking too few trades
Traders are scared of taking too many trades
Traders are scared of consecutive losses
Traders are scared of exiting too early
Traders are scared of exiting too late
Traders are scared of being called a loser
Traders are scared of not being able to trade anymore
These fears cause traders to ignore their trading rules and act
emotionally. For instance, the fear of having a losing trade
causes us to exit prematurely with tiny profits. The fear of
having a losing session causes us to set an unrealistic target to
get back what we lost earlier.
Although fear is correctly identified as part of a trader’s
psychological problem, talking about it seldom leads to any
improvement in a trader’s psychology. When we discuss the
psychological difficulties of trading, we often lapse into abstract
ideas of how to improve our mental resilience to enhance
trading performance. Working through such uncollected
thoughts might be interesting but hardly beneficial.
To address our psychological demons effectively, we need to go
one step back and understand the reasons for our fear. This will
empower us with a solid foundation to recognise that our fears
are not compatible with the market, and that our response to
fear is irrational. Then, we need to go a step forward and put in
place measures to help us act correctly when we are fearful.
Thus, we have a two-pronged approach.
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First, we need to understand why most of our fears are
unfounded. This step is aimed at eliminating the fear factor in
our trading process.
However, we are humans and we can never entirely uproot fear
from our minds. That’s okay, because we should not ignore fear
entirely. Fear is an instinct that heightens our senses to help us
protect ourselves. This also leads us to the second part of our
solution to fear.
The second part relates to our response to fear. We must
condition ourselves to react to fear constructively and not
destructively. Do not underestimate this mental conditioning.
Without mastering your reaction to fear, the slightest
destructive element is a potential start to a downward spiral
that could wipe out your trading account.
7.5.1 - Psychological Foundation
To manage your trading psychology, there are three things you
should know.
1. It is natural to feel fearful.
2. The market does not care about how you feel.
3. It is our response to fear that matters.
It is natural to feel fearful. Our mind is programmed to fear
uncertainty, loss, and pain. The feeling of fear protects us by
heightening our senses. In fact, psychologists have suggested
that humans have only a small set of innate basic emotions and
that fear is one of them.
Hence, we should not think that feeling apprehensive is wrong
and attempt to deny feelings of fear. Instead, as you will see, in
order to trade well, we need to embrace fear.
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Fear is necessary for profitable trading. We depend on other
market participants feeling fearful to make our profits. If every
market player is perfectly rational and is not affected by their
emotions, the market would be much more efficient than it is. It
would be much harder to make money out of it. The very fact
that humans act emotionally undermines the efficient market
hypothesis theory.
Fear is more desirable than being fearless. Fearless traders are
either gamblers or arrogant traders who think they will always
win. To avoid certain ruin in your trading career, make friends
with fear.
The market does not care about how you feel. The problem
with fear is not that we experience it. The reality is that the
market does not care. While your every step is drenched in fear,
the market does nothing in response to it.
By nature, we are afraid of uncertainty and our fear stems from
a craving for certainty. However, the market is nothing but
uncertain. This fundamental difference between what we crave
for and what the market epitomises is the root of our
psychological troubles.
As mentioned above, as traders, we are fearful of dozens of
things. How does fear cause us to flout our trading rules?
Regardless of the exact rule you flouted or the excuses you give
yourself, it always boils down to one root cause - you want
something that the market cannot give.
“I want the next trade to be a winner. I’m afraid to be labelled a
loser.”
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The market cannot promise that because trades are governed
by probabilities and not certainties. They are not governed by
your desires.
“I don’t want to lose. I’m afraid of losing.”
The market cannot promise that because it changes.
“I want to make up for the losses earlier in the session. I’m
scared of having a losing session.”
Again, the market cannot promise that. The profit potential in
the later part of the session does not increase simply because
you need to have a profitable session.
We want certainty and that is what the market is unable to give.
If you act like you are going to get a guaranteed outcome from
the market, you will suffer.
It is important to stay away from the quest to buy at market
bottoms and sell at market tops. The market will never let you
do that consistently. A quest for perfection is bad for a trader’s
health and wealth; a quest for positive expectancy with prudent
position sizing for scaling up is excellent for both. The real quest
is to find a positive expectancy approach that works for you.
It is our response to fear that matters. We know that we
experience fear in the markets. However, we must realise that it
is not the feeling of fear that destroys us. It is our response to
fear that is destructive.
For instance, after a series of losses in the morning, I am scared
of having a losing session. But in fact, everything is still cool. I
still have money in my trading account. I have not engaged in
destructive actions.
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Fear, as a feeling, is not destructive.
However, in response to that fear, I decide to ignore my position
sizing rules and double my trading size for the next trade,
hoping that I can make up for earlier losses. Then, I end up
blowing up my trading account as the market goes against me
again in the afternoon.
This response to fear is destructive.
Fear is neutral. It is our response to it that determines its
impact on our trading performance. Each time I feel fearful, I
can take a step back and rely on my rules. Or I can choose to
ignore my rules and behave destructively. Fear can be a
warning to help us improve our trading or an impetus for
misbehaviour.
“We have met the enemy and he is us.”
Walt Kelly, Pogo
7.5.2 - Practical Strategy
Other than understanding the theoretical underpinnings of our
psychological risks, we also need a practical method to manage
our psychological risks. For the method to be effective in realtime trading, it must be specific and not overly complicated.
In most trading books and online sources, you will find lists of
maxims related to trading psychology. A sample list includes:
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
Stay mentally focused while trading.
Follow your system with no questions asked.
Seek consistency over profits.
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There are dozens of such maxims everywhere.
I will not repeat them, not because they are untrue. In fact, I
have mentioned a handful throughout this series. They are
mostly great advice. They are fantastic for anyone who can
actually follow them. However, most traders do not benefit from
simply reading them.
Another reason for not repeating them is that they are freely
available online and from other sources.
Instead, I want to show you a tangible plan for managing fear.
This plan’s objective is to help you to improve your emotional
awareness and to react to your emotions constructively.
Trading Emotion Journal
Before entering or exiting a trade, ask yourself these three
questions.
1. Am I scared?
2. Why am I scared?
3. How should I respond to this fear constructively?
Start a Trading Emotion Journal and answer these questions.
(There is a template for the journal in the Toolkit.)
Am I scared?
If you are scared, turn off your trading platform immediately, no
questions asked.
If you are fearful and do not know how to deal with that fear,
you will not trade well. Most likely, you will be gambling instead
of trading. So don’t bother.
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Traders working in a bank or a proprietary trading firm must
trade and must be profitable. Or else, they will be asked to go.
While they enjoy superior infrastructural and financial support,
they face immense pressure to perform on other people’s terms.
Even when they are not in the best condition to trade, they have
no choice but to risk it. That circumstance is obviously suboptimal.
However, as individual traders, our greatest advantage is the
ability to choose whether or not to trade. We have no
organisational pressures upon us. We have every reason to
make full use of this flexibility. By choosing not to trade when
you are not feeling up to it, you gain a clear advantage over
institutional traders.
“You have power over your mind - not outside events.
Realize this, and you will find strength.”
Marcus Aurelius, Meditations
You trade only when you are emotionally prepared. You trade
when you are “in the zone”. Institutional traders trade because
they are expected to. They trade even when they are not “in the
zone”. Who do you think will do better?
This is exactly why you must exercise the option of not trading
when you are not emotionally ready. Don’t feel compelled to
trade. If you feel compelled to trade, you are giving up a key
advantage over institutional traders. Given their superior
technical resources, this is an advantage you cannot afford to
waste.
Hence, the first step is to learn to stop trading when you are
scared and don’t know why.
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The next step requires us to embrace our fears. Think about the
reasons behind your fear. Given that you have worked your way
to this final part of the book, finding the answer should not be
difficult.
In the sections below, you will find sample entries of a Trading
Emotion Journal.
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Entry 1
Why am I scared?
I am scared that the next trade will be a loser. I want it to be a
winner.
But I know that the market cannot guarantee that it is a winner.
So why am I hoping for something that the market cannot give?
Because if the next trade is a loser, my trading account will fall
below the minimum amount I need to trade.
Clearly, this fear stems from a lack of trading capital.
How should I respond to this fear constructively?
Stop trading and build up more risk capital. Resume trading only
after you’ve accumulated sufficient risk capital. Alternatively,
look for a market that I can trade with less capital (for e.g.
micro lots in spot forex).
A destructive response would be to continue trading and exit
once my position shows a small profit. Exiting with a small profit
might increase my winning probability. However, due to a
proportionately larger decrease in my reward-to-risk ratio, the
expectancy of each trade would decrease.
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Entry 2
Why am I scared?
I am afraid that if I exit now, I might lose out on a huge chunk
of profits. I want to exit at the best possible position and get the
largest possible profit.
But I know that there is no perfect exit. More importantly, I
know that I do not need the perfect exit to achieve positive
expectancy. So why am I hoping for the perfect exit? Because I
saw that in my previous trade, the market went much further
than I targeted and I missed out on a huge chunk of profits.
This fear of losing out (or greed) is the result of a single recent
experience.
How should I respond to this fear constructively?
I should not change my trading plan because of one isolated
trade. Moreover, even if I want to change my exit plans, I have
no idea how to.
Let profits run? But how? Should I push my target 20 ticks out?
Should I push it to the next support level? Should I throw on a
moving average and let it guide my exit? I have no real
solution.
Hence, I should not change my exit plan, for now.
However, it might be a signal for me to start exploring if setting
my targets more aggressively produces better results. This is an
excellent chance for me to implement virtual decisions (as
discussed in 6.4.4 - Improving Expectancy) to test the impact of
setting more aggressive targets.
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A destructive response would be to cancel the target order and
attempt to let my profits run. However, without a concrete plan
dictating how exactly I should let my profits run, I would end up
confused and doubting myself with every price tick.
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Entry 3
Why am I scared?
I did not get any trading opportunities in the earlier part of the
session. I am afraid that I might not get a chance to trade.
But I know that it is better to take fewer high quality trades
than to take more low quality ones. So why am I scared that I
might not get a chance to trade? Because I feel that I am
missing out on the market action. How can I call myself a trader
if I am not trading?
The fear in this case originates from the thinking that a trader
must be trading at all times.
How should I respond to this fear constructively?
My objective is not to take trades. My objective is to take trades
with positive expectancy.
Hence, instead of being tempted by inferior setups, I should
congratulate myself for being selective and look forward to the
next high quality setup.
A destructive response would be to compromise my trading
rules and take trades that are inconsistent with my trading
strategy. These are rogue trades that would inevitably lead me
into self-doubt issues.
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The fears discussed above are clearly not exhaustive. The
objective of the three questions is to enhance your emotional
awareness while trading. Becoming aware of your feelings and
asking the right questions can uncover a lot about your trading
psychology.
Fear is obvious. You can always detect it. When you start to
hope and pray, you are fearful. When you start to hold your
breath, you are fearful. This is why the feeling of fear is the best
starting point for monitoring our psychological risks and
enhancing our emotional awareness.
The Ultimate Litmus Test
In chemistry, a litmus test distinguishes acid from alkali with a
single liquid drop. In politics, it is a simple question to
determine a candidate’s attitude towards contentious issues.
In both cases, a litmus test is a simple test with great clarifying
implications.
A major theme in a trader’s emotional issues is the constant
conflict between the trader’s desire for certainty and the
market’s probabilistic nature.
Truly understanding and accepting the market’s probabilistic
nature is the key to minimising your psychological woes.
Based on this understanding, I have formulated an ultimate
litmus test to help you decide if you should be taking a trade.
The test has just one simple question. Before taking each trade,
ask yourself:
Will I regret taking this trade if it turns out to be a loser?
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This is a simple but powerful question. It drills into the heart of
your market understanding and your rationale/motivation for
wanting to take each trade.
If you took a trade that was consistent with your trading plan,
you should not regret taking the trade even if it results in
losses. A trader’s job is to execute his trading plan. If you have
done so, you have no cause for remorse. The loss incurred is
merely a necessary cost of your trading business.
Doing the right thing, taking the right trade, unaffected by your
emotions, is something that is independent of the trade
outcome. If you understand the probabilistic nature of the
market, you will understand this principle. Thus, if you can
answer “yes” to the ultimate litmus test, then you may take the
trade.
“Every battle is won or lost before it is ever fought.”
Sun Tzu, The Art of War
However, if you rejoice with winning trades and regret taking
losing ones, then you are not ready to embrace the probabilistic
nature of the market. You are not ready to trade. In fact, you
have the mind-set of a gambler.
The psychology of trading is similar to the psychology of
gambling. However, there is one profound difference.
A trader’s mind is geared towards allowing long-term
expectancies to emerge. Traders want luck to even itself out in
the long-run, which means that individual outcomes are
unimportant.
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On the other hand, a gambler’s mind is focused on not wanting
the long-term expectancies to emerge. Gamblers want luck to
be on their side, and individual bet outcomes are important to
them. If luck evens out, the gambler will inevitably end up
broke.
Let’s say that you took a trade that was consistent with your
trading plan. It resulted in a loss, and you regret taking it. You
should not regret taking a trade merely because it resulted in a
loss. Losses are expected. Hence, if you regret taking that
trade, you have not fully comprehended the probabilistic nature
of trading. You should not be trading.
Now, let’s say that you took a rogue trade that was profitable.
Despite the profits, you should regret taking it because it is a
rogue trade. It is inconsistent with your trading plan and you
know that you will not be able to replicate such trades
consistently.
After entering a trade, you should be proud that you have
entered a good trade according to your rules and should not be
praying for the success of the trade.
The key here is that if a trade is worth taking, it is worth taking
regardless of its outcome.
ULTIMATE LITMUS TEST
Will I regret taking this trade if it turns
out to be a loser?
Asking yourself this question will keep you from taking rogue
trades and remind you of the probabilistic nature of trading.
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7.5.3 - The Final Determinant
Ultimately, the burden of managing psychological risks rests
squarely on you, the trader.
The first step is to be truthful to yourself. If you stay in denial
and refuse to take steps to react constructively to your
emotions, nothing can help you.
Indeed, there are various methods to manage trading
psychology like getting a trading buddy/mentor, using
computers to control your risk with hard limits, and even with
neuro-linguistic programming.
Yet, no method is impervious to your overriding. You can stop
employing these methods as quickly as you adopted them.
You, the trader, are the final determinant.
PSYCHOLOGICAL RISKS

Start a Trading Emotion Journal
(Template included in the Toolkit)

Employ the Ultimate Litmus Test

Be truthful to yourself
7.6 - Integration of Risks
Up to this point, we have been discussing each risk in isolation
for clarity. However, in reality, risks are often inter-related. To
understand the overall risk context, we need to pay attention to
the relationships among the different risks.
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This is hardly a new concept. Throughout the book, as we speak
of assessing trade risks, we also discuss how psychological risks
might affect them. A good example is found in Chapter 2.3 The Wrong Way to Place Stop-losses, where we discussed how
the fear of losing can affect our stop-loss placement.
In particular, you will find that psychological risk is deeply
integrated with other risks. The following are classic examples
showing how financial risk is tied to emotional risk.
We have discussed using a simulated drawdown figure as our
basis for computing the amount of trading capital we need.
However, that is only the statistical aspect.
The amount of trading capital we need to trade also depends on
our emotional considerations. Your trading capital must be large
enough so that consecutive losses do not take a toll on your
emotions. Even if your trading capital remains statistically
healthy, if you become afraid because of the magnitude of
drawdown, then you might need a larger amount of trading
capital.
The same influence runs the other way. If you have a technically
sound position sizing model that you truly understand, it is less
likely that you will experience stress when you suffer
drawdowns.
We have also discussed the issue of living expenses and the risk
of volatile income for full-time traders. Traders who are stressed
by insufficient income are more susceptible to their emotional
whims. When you feel the heat to earn more or enough to pay
the bills, it’s easy to get tempted to overtrade and take on a
large (unsafe) position size.
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Understanding how risks are integrated will only come with
actual trading experience. However, this is an important area to
bear in mind as you design a risk-based trading approach.
7.7 - Conclusion
First, deal with intrinsic and external risks separately.
Remember that external risks do not give you any trading edge.
They merely prevent your trading edge (if any) from
deteriorating. Hence, manage your intrinsic risk first and make
sure that you have the ability to find trades with positive
expectancy.
Next, recognise that risk management is a process. There is no
destination. You need to constantly evaluate the effectiveness of
your controls. You also have to watch out for new risk factors
that might warrant intervention.
Even for the risks that you have decided to accept, you need to
continue monitoring them in case they increase to an extent
that you find unacceptable. Moreover, your access to resources
(financial, technological, and intellectual) might change over
time. Some risks might become harder or easier to mitigate.
This might cause you to re-evaluate your original risk decisions.
I recommend performing a risk review (i.e. update your Risk
Management Cards) every two to three months.
I am not professionally trained to manage risks in the way
enterprise risk managers or actuaries are. In addition, I am not
an expert with computers, statistics, or psychology. The
perspectives above are simply how I think about the various
risks I face as a professional trader. While they are generally
applicable to individual traders, as I have mentioned time and
again, you must consider them within your own risk
environment.
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Remember that the best traders are often the best risk
managers.
Risk-Based Trading

Manage your financial and operational
risks with Risk Management Cards

Start a Trading Emotion Journal and
react constructively to your emotions

Review your risk management
measures every two to three months
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Chapter 8 - End of the Beginning
We have reached the end of the book. However, it is really just
the beginning for some of you.
Depending on your level of trading experience, you would have
picked up varying ideas from this series.
For new traders, I’m sure that this book and the Toolkit contain
everything you need to start day trading with a realistic and
sound foundation.
For experienced traders, I’m certain that you will be able to
integrate at least some of the price action concepts into your
trading. The Toolkit documents were built with Microsoft Excel
which is a common yet powerful software. This is so that you
can adapt it for your own use easily.
I expect you to agree with some parts of the trading framework
we discussed and disagree with others. That is great, and
unsurprising. Most successful traders I know are fiercely
independent. It also shows that you have been engaging the
ideas actively. I hope that you’ll continue to learn and evolve as
a trader.
I have benefitted immensely from writing this series. It has
allowed me to crystallise my trading approach and improve my
trading performance. I want to thank you for giving me this
opportunity.
“We cannot teach people anything; we can only help them
discover it within themselves.”
Galileo Galilei
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Galileo got it right. I am not teaching you much. Ultimately, you
must find the successful trader within yourself.
I wish you all the best in tackling the challenge of day trading
with price action.
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