Probability-based Trading Using Regression Channels
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Speaker Profile: Greg Shtock, Investor's Business Daily Toronto Group Organizer.
Greg is an active personal investor who is managing his own portfolio and trading futures,
options, stocks and exchange-traded funds (ETFs). He developed and follows a well-defined set
of rules. These rules are based on the trend following principles, risk management and the
necessity of having a detailed plan prior to initiating any investment position.
Greg didn’t begin his career in the financial industry. Over 20 years ago, while working full time
as an engineer, he began to manage his own investments. He carefully studied the markets,
tested different investment methods and discovered what methods work, what methods don’t
work and, most importantly, why. Today, he shares his experience, insights, and passion with
others by teaching courses and seminars such as the Practical Personal Investing course at
Ryerson LIFE Institute.
Canadian Society of Technical Analysts, November 25, 2014, Monthly Meeting, Presented by Greg Shtock
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Canadian Society of Technical Analysts, November 25, 2014,
Monthly Meeting, Presented by Greg Shtock
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Canadian Society of Technical Analysts, November 25, 2014,
Monthly Meeting, Presented by Greg Shtock
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Probability-based Trading Using Regression Channels
TC2000 chart, Stock X, Technical Analysis
Canadian Society of Technical Analysts, November 25, 2014, Monthly Meeting, Presented by Greg Shtock
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Probability-based Trading Using Regression Channels
TC2000 chart, Stock X, Technical Analysis
Canadian Society of Technical Analysts, November 25, 2014, Monthly Meeting, Presented by Greg Shtock
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Probability-based Trading Using Regression Channels
TC2000 chart, Stock X, Technical Analysis
Canadian Society of Technical Analysts, November 25, 2014, Monthly Meeting, Presented by Greg Shtock
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My Journey into the Financial World.
 I started my journey by reading almost every
book available on the subject of investing. I
attended meetings such as this one and studied
different strategies related to the investing
methodologies.
 It included a wide range of strategies from
Warren Buffett's 'Buy-And-Hold' Strategy to Day
Trading, Fundamental and Technical Analyses, etc.
 Each strategy looked great in theory.
Being an engineer and a practical man, I did not
stop at the academic level. I tried each and every
strategy in the real world of investing.
Canadian Society of Technical Analysts, November 25, 2014, Monthly Meeting, Presented by Greg Shtock
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My Journey into the Financial World.
However, practical application of these theories revealed
very different results. NONE of the methods worked all
the time.
Former Federal Reserve Board Chairman, Alan
Greenspan, often used the phrase “Irrational
Exuberance” to describe the financial markets.
Dennis Gartman once said:
“The market can remain illogical far longer
than you or I can remain solvent.
Canadian Society of Technical Analysts, November 25, 2014, Monthly Meeting, Presented by Greg Shtock
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My Journey into the Financial World.
To be a successful investor you need to have an edge.
Mark Douglas: "An edge is nothing more than an indication of a higher
probability of one thing happening over another.“
http://www.markdouglas.com/
Van Tharp, Probabilities and Expectancy
http://www.vantharp.com/tharp-concepts/expectancy.asp
Expectancy along with position sizing are probably the two most important
factors in trading/investing success.
Expectancy = (Probability of Win * Average Win) – (Probability of Loss *
Average Loss)
Canadian Society of Technical Analysts, November 25, 2014, Monthly Meeting, Presented by Greg Shtock
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My Journey into the Financial World.
The pinnacle of my academic journey was when I went to the extreme of
developing computer codes such as the Kelly’s formula.
His paper dealt with the fact that in the probability theory a formula could be devised to determine the
optimal size for a series of bets to minimize risk and maximize expected returns.
In probability theory and intertemporal portfolio choice: the Kelly criterion, Kelly strategy, Kelly formula,
or Kelly bet is a formula used to determine the optimal size of a series of bets. In most gambling and
some investing scenarios, the Kelly strategy will do better in the long run than any essentially different
strategy. For simple bets with two outcomes, one involving losing the entire amount bet, and the other
involving winning the bet amount multiplied by the payoff odds, the Kelly bet is:
where:
• f* is the fraction of the current bankroll to wager, i.e. how much to bet;
• b is the net odds received on the wager ("b to 1"); that is, you could win $b
(on top of getting back your $1 wagered) for a $1 bet
• p is the probability of winning;
• q is the probability of losing, which is 1 − p.
From <http://en.wikipedia.org/wiki/Kelly_criterion>
Canadian Society of Technical Analysts, November 25, 2014, Monthly Meeting, Presented by Greg Shtock
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Probability-based Trading Using Regression Channels
Then I realized the validity of Albert Einstein’s following statement:
"Any intelligent fool can make things bigger and more complex. It
takes a touch of genius and a lot of courage to move in the opposite
direction."
Today I am a big believer in the “Keep It Simple, Stupid” (KISS) principle.
I always have a detailed plan before initiating any new position.
It includes:
Technical Analysis and Regression Channels which are the essential
part of probability-based trading.
Stop loss and target prices.
Risk / Reward Ratio - it measures probabilities of expected returns of
an investment relative to the amount of risk undertaken to capture
these returns.
Canadian Society of Technical Analysts, November 25, 2014, Monthly Meeting, Presented by Greg Shtock
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Probability-based Trading Using Regression Channels
 Fundamental analysis involves analyzing financial
statements, management, competitive advantages,
state of the economy, interest rates, earnings forecast,
credit risk, cash flow, divided, P/E ratio (price-toearnings ratio), PEG ratio, debt-to-equity ratio, etc.
 Based on fundamental analysis, investors can
determine whether it is a value stock, a growth stock,
or a stock that you should stay away from.
 Technical Analysis maintains that all information is
already reflected in the stock price. Trends “are your
friend.” The technical analyst does not care what the
“value” of a stock is.
 Stock prices trend directionally, i.e., up, down, or
sideways. The basic definition of a price trend was
originally put forward by the Dow Theory.
There is NO investor’s Holy Grail or a crystal ball.
We can NOT predict future prices or market moves.
Practical Personal Investing, Session 4, presented by Greg Shtock
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Probability-based Trading Using Support / Resistance
Example: Support Line Case trading Forex Trading USD.CAD
Standard Deviation (SD)
Target 1.15000
Current Price 1.13434
Regression Line
Support
Standard Deviation
(SD)1.12504
Potential Loss: 1.13434 – 1.12504 = 0.0093
Potential Gain: 1.15000 - 1.13434=0.01566
Reward to Risk Ratio: 0.01566 / 0.00894 = 1.68
Reward / Risk Ratio 1.68 to 1
Canadian Society of Technical Analysts, November 25, 2014, Monthly Meeting, Presented by Greg Shtock
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Probability-based Trading Using Regression Channels
The concepts of support and resistance levels are undoubtedly the most acceptable and
widely used among investors, traders and technical analysts. However, they have their own
challenges.
 It is based on a single data point. Typically, you look at the chart and choose one point
where you think the support and resistance is.
 As such, it is also subjective. Different analysts may pick up different points.
 Because it is so widely used everyone knows and talks about it. Therefore, you have NO
edge over everyone else. In fact, you are at a disadvantage because the “big guys” use it
to their advantage.
Probability-based Trading Using Regression Channels solves these problems because:
 It is a statistical analysis of a large number of data points.
 It is objective because it calculates the results without the user’s opinion.
 It is not popular and rarely used. Most amateur and even professional traders have never
heard of this methodology.
 And finally it is NOT a “holy grail”. However, it does give you enormous advantage over
other traders and puts the odds in your favour.
Canadian Society of Technical Analysts, November 25, 2014, Monthly Meeting, Presented by Greg Shtock
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Probability-based Trading Using Regression Channels
Definitions: Linear Regression Line
Linear regression is a common statistical data analysis tool. Linear Regression Lines use the
least squares method or other methods to plot a straight line through prices so as to
minimize the distances between the prices and the resulting line.
This line could be considered as the "equilibrium“ of all data points. It acts like a “magnet”.
Prices move above or below the line would be “pulled” back to the equilibrium mean point.
It is in essence the reversion to the mean mechanism.
Canadian Society of Technical Analysts, November 25, 2014, Monthly Meeting, Presented by Greg Shtock
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Probability-based Trading Using Regression Channels
Definitions: Standard Deviation (SD) and Bell Curve
In statistics and probability theory, the Standard Deviation (SD), represented by the Greek
letter sigma, σ, measures the amount of variation or dispersion from the average.
In probability theory, the normal (or Gaussian) distribution or the bell curve, is a commonly
occurring continuous probability distribution—a function that tells the probability that any
real observation will fall between any two real limits or real numbers.
http://en.wikipedia.org/wiki/Normal_distribution
Examples of power and importance of Statistical Process Control (SPC) in mass production
environment. We can apply this proven method to trading.
Canadian Society of Technical Analysts, November 25, 2014, Monthly Meeting, Presented by Greg Shtock
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Probability-based Trading Using Regression Channels
Example: Forex Trading USD.CAD
Standard Deviation (SD)
Regression Line
Standard Deviation (SD)
Canadian Society of Technical Analysts, November 25, 2014, Monthly Meeting, Presented by Greg Shtock
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Probability-based Trading Using Regression Channels
Example: Regression Channels Case Trading Forex Trading USD.CAD
1 Standard
Deviation (SD)
Line
Target 1.27865
Regression Line
Current Price 1.09501
SD Value 1.08786
(Stop Loss)
1 Standard Deviation (SD) Line
Potential Loss: 1.09501 – 1.08786 = 0.00715
Potential Gain: 1.27865 - 1.09501 = 0.18364
Reward to Risk Ratio: 0.18364 / 0.00715 = 25.7
Reward / Risk Ratio 25.7 to 1
Canadian Society of Technical Analysts, November 25, 2014, Monthly Meeting, Presented by Greg Shtock
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Probability-based Trading Using Regression Channels
What this reward / risk ratio means?
 In the case of the support line example, this ratio was 1.68. This means on average, after a number of
trades were made following this system, you will have gained $1.68 per trade when you are right vs $1
loss when you are wrong.
 In the illustration of the regression channels case, this ratio was 25.7, which means you would have
made on average $25.7 on each successful trade vs. $1 loss on trade that did not work out.
 In real life, based on my experience, it is difficult to find trades with 25:1 ratio. On the other hand, I
would NOT typically initiate a trade with 1.68:1 ratio or less.
 From a practical point of view, I would find trades with ratio between 3:1 to 5:1 or higher.
 What does it mean if trades have 3:1 ratio? It means that even if you are wrong 50% of the time or half
of your trades are losers, you will make money !!!
Canadian Society of Technical Analysts, November 25, 2014, Monthly Meeting, Presented by Greg Shtock
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Canadian Society of Technical Analysts, November 25, 2014, Monthly Meeting, Presented by Greg Shtock
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