A Practical
Introduction
to Day Trading
A Practical
Introduction
to Day Trading
By
Don Charles
A Practical Introduction to Day Trading
By Don Charles
This book first published 2018
Cambridge Scholars Publishing
Lady Stephenson Library, Newcastle upon Tyne, NE6 2PA, UK
British Library Cataloguing in Publication Data
A catalogue record for this book is available from the British Library
Copyright © 2018 by Don Charles
All rights for this book reserved. No part of this book may be reproduced,
stored in a retrieval system, or transmitted, in any form or by any means,
electronic, mechanical, photocopying, recording or otherwise, without
the prior permission of the copyright owner.
ISBN (10): 1-5275-1599-0
ISBN (13): 978-1-5275-1599-4
TABLE OF CONTENTS
Preface ........................................................................................................ ix
Chapter One ................................................................................................. 1
General Introduction
1.0 Trading ............................................................................................. 1
1.1 Trading Styles .................................................................................. 2
1.2 Portfolio Allocation ......................................................................... 4
1.3 Profit Loss Ratios............................................................................. 5
1.4 Book Objectives ............................................................................... 5
1.5 Outline of Book ............................................................................... 6
1.6 Summary Insight .............................................................................. 6
Chapter Two ................................................................................................ 7
Day Trading
2.0 Introduction...................................................................................... 7
2.1 Where Assets are Traded ................................................................. 7
2.1.1 The Forex Market .................................................................... 8
2.2 Day Trading ................................................................................... 10
2.3 Opening an Account ...................................................................... 13
2.4 Important Questions to Consider Before Trading .......................... 18
2.4.1 Types of Orders ..................................................................... 20
2.4.2 Level 1 and Level 2 data ....................................................... 22
2.5 How to Find Stocks to Trade ......................................................... 24
2.5.1 Stock Scanners ...................................................................... 25
2.6 Creating a Watch-List .................................................................... 27
2.6.1 Top-Down Analysis .............................................................. 27
2.6.2 Fundamental Analysis ........................................................... 28
2.6.3 Technical Analysis ................................................................ 32
2.7 Summary Insight ............................................................................ 32
vi
Table of Contents
Chapter Three ............................................................................................ 33
Technical Tools and Technical Analysis
3.0 Introduction .................................................................................... 33
3.1 Technical Analysis ......................................................................... 33
3.2 Candlesticks ................................................................................... 34
3.2.1 Heikin-Ashi Candlestick ....................................................... 38
3.3 Types of Markets ........................................................................... 38
3.4 Chart Patterns ................................................................................. 39
3.4.1 The Elliott Wave Theory ....................................................... 49
3.5 Oscillators ...................................................................................... 54
3.5.1 Momentum Oscillator............................................................ 55
3.5.2 On-Balance-Volume.............................................................. 55
3.5.3 Relative Strength Index ......................................................... 55
3.5.4 Relatove Volume ................................................................... 56
3.5.5 Money Flow Index ................................................................ 56
3.5.6 Stochastic Oscillator .............................................................. 57
3.5.7 Fibonacci Retracement Levels .............................................. 58
3.5.8 Force Index ............................................................................ 60
3.6 Moving Averages ........................................................................... 62
3.6.1 Simple Moving Average ....................................................... 62
3.6.2 Exponentially Weighted Moving Average ............................ 65
3.6.3 Volume Weighted Moving Average ..................................... 66
3.6.4 Moving Average Convergence Divergence .......................... 66
3.7 Bollinger Bands: Another Technical Indicator .............................. 67
3.8 Linear Regression Models ............................................................. 68
3.9 Summary Insight ............................................................................ 76
Chapter Four .............................................................................................. 77
Trading Strategies
4.0 Introduction .................................................................................... 77
4.1 Trading Strategies .......................................................................... 77
4.1.1 Crossovers ............................................................................. 78
4.1.2 Moving Average Envelopes and Bollinger Bands................. 82
4.1.3 Momentum ............................................................................ 82
4.1.4 Volatility Breakouts .............................................................. 84
4.1.5 Reversals ............................................................................... 84
4.1.6 Events Trading ...................................................................... 85
4.1.7 Heikin-Ashi ........................................................................... 88
4.1.8 Elliott Wave Based Trading .................................................. 88
4.2 Evaluating the Trading Strategy .................................................... 90
4.3 Summary Insight ............................................................................ 91
A Practical Introduction to Day Trading
vii
Chapter Five .............................................................................................. 93
Risk Management
5.0 Introduction .................................................................................... 94
5.1 Types of Risk ................................................................................. 94
5.1.1 Market Risk ........................................................................... 94
5.1.2 Liquidity Risk ........................................................................ 95
5.1.3 Concentration Risk ................................................................ 96
5.1.4 Credit Risk ............................................................................ 98
5.1.5 Inflation Risk ......................................................................... 99
5.2 When to open a Position ................................................................ 99
5.3 When to close a Position .............................................................. 100
5.4 Position Sizing and Balancing Risk ............................................. 104
5.5 Common Mistakes ....................................................................... 107
5.6 Summary Insight .......................................................................... 107
Chapter Six .............................................................................................. 109
The Average Trading Day and General Conclusion
6.0 Introduction .................................................................................. 109
6.1 Mechanical Trading Systems ....................................................... 109
6.2 The Average Trading Day for the Informed Stock Trader ........... 112
6.3 A Practical Mechanical Trading System for Trading Currencies ... 114
6.4 Trading Plan ................................................................................. 115
6.5 Conclusion ................................................................................... 116
References ............................................................................................... 119
PREFACE
Many individuals enter financial markets with the objective to earn a
profit from capitalizing on price fluctuations. However, many of these new
traders lose their money in trading. The reason for this is often because
these new traders lack any fundamental understanding of financial
markets, they cannot interpret any data, and they have no strategy for
trading.
Trading on financial exchanges is really about deploying strategies to
systematically generate gains, and managing risks to minimize losses.
Indeed, successful traders do have objective strategies which they have
proved to be effective in granting them more financial gains than financial
loss.
The purpose of this book is to help a potentially uninformed retail
trader or inquisitive reader understand more about financial markets, and
assist them in the acquisition of the technical skills required to profit from
trading. This book is a beginner’s guide to trading. It focuses mainly on
trades of stocks and currencies on Exchanges. While some of the analysis
can be useful for other assets such as futures, commodities, and options,
the analysis will not always be relevant for such markets.
The first chapter of this book introduces the reader to some key
concepts in the trading industry. The distinction is made between trading
and investing. The second chapter introduces the reader to day trading. It
informs the reader of the basic information that they need to know before
they attempt to trade in any market. The third chapter introduces the reader
to Technical Analysis. It informs how to interpret charts, and how to
recognize patterns in asset prices. The fourth chapter considers some basic
trading strategies which may be used by retail traders. The fifth chapter
considers how a retail trader may manage risk. Finally, the sixth chapter
concludes with a practical example of a trading strategy.
CHAPTER ONE
GENERAL INTRODUCTION
1.0 Trading
Trading is the practice of buying and selling assets over a short-term
period. Assets here refer to any financial security, commodity, or currency
that an economic agent purchased. Market participants that practice
trading are referred to as traders.
A distinction can be made between a retail trader and an institutional
trader. A retail trader refers to a trader that trades independently for
themselves. An institutional trader refers to a trader that is employed by a
financial institution (for example a commercial bank, investment bank, or
hedge fund) and perform trading activities as part of their job description.
Trading is distinct from investing. Investing refers to the practice of
purchasing assets with the objective of gradually growing wealth from the
asset over a period of time. The market participant may purchase a range
of assets1, and hold the portfolio2 of assets over a period of time. While the
price of the assets in the portfolio may fluctuate over time, the goal of the
economic agent is to ride out the short-term price fluctuations and
gradually earn a positive return3 over a period of time. Market participants
that engage in the practice of investing are typically referred to as
investors.
While investors seek to earn a return, perhaps with a range of 5% to
15%, over a year, traders seek to make such returns over a much shorter
time period, ranging from a day to a few weeks. Traders try to take
advantage of short-term price fluctuations in assets. When they execute
1
Some of these assets may include stocks, bonds, mutual funds, exchange traded
funds and other investment instruments.
2
A portfolio is a group of assets.
3
The return is the profit from an asset. It is gain (loss) from price increases
(decreases) plus the gains from dividends if any are paid.
Chapter One
2
trades, they try to buy assets and sell them just a few dollars or cents
higher. However, the make large profits by trading large volumes of assets
with each trade.
Traders can be categorized basis upon their style of trading. The next
section will explore different trading styles.
1.1 Trading Styles
In summary, trading styles may be categorized into the following:
x
x
x
x
Position trading;
Swing trading;
Scalping; and
Day trading.
Position trading is where the position is held by the economic agent for
several weeks to several months. Position traders first try to identify
trends4 in the price of assets. If they expect a bullish trend5, then they
would go long6 on the asset. If they detect a bearish trend, they may short
sell7 the asset.
Position traders may not necessarily try to forecast the future prices of
the asset, rather they try to ride the ‘wave’ of the trend which has been
firmly established, and benefit from the overall movement of a stock in a
market. Position traders typically exit a position when the trend breaks.
4
Here a trend refers to a sustained movement in the price of an asset.
A bullish trend is an upward trend or upward price movement. The opposite of a
bullish trend is a bearish trend. A bearish trend is a downward price movement.
6
Going long refers to buying an asset.
7
Short selling refers to where an economic agent has sold an asset that they do not
own. In essence, they have borrowed the asset from their broker and sold it.
However, eventually the economic agent would have to repurchase the asset,
perhaps when it falls to a lower price, and return the asset to their broker. When the
economic agent returns the asset to the broker, it is referred as a ‘cover’. It is
important to note, the US Securities and Exchange Commission adopted a Short
Sale Restriction (SSR) rule since February 2010 (US SEC 2016). Once this rule is
activated, economic agents can only short sell the asset once the price is going up.
This rule was devised in order to prevent crashes from occurring as a consequence
of too many economic agents short selling an asset while its price is declining.
5
General Introduction
3
Swing trading is where a market participant holds a position for a few
days, to a few weeks. Once the trader holds more than few weeks, it is
called position trading. Swing trading is slower paced than day trading
since the time frame for holding trades is longer. It is very important that a
swing trader have a trading strategy, as stocks will be moving up and
down, but they will not be always available to constantly monitor the
market like a day trader.
Scalping refers to where traders’ long (or short) assets, hold them for a
few seconds or minutes then close the position. Scalpers try to exploit
small moves in price by trading large volumes of the asset over a very
short period of time. Scalpers try to take advantage of the volatility8 in the
market.
Day trading refers to the practice of buying and selling assets in the
same day. Positions are not held overnight. All positions are closed within
the same day. Day traders try to make profits by exploiting the volatility in
an asset price in a day. Like scalpers, day traders profit by moving a large
volume of stocks. Day traders’ trading interval is the active hours of a
trading day, whereas scalpers’ trading intervals range from a few seconds
to a few minutes. When a trader opens and closes their position on an asset
from an account, it is referred as a round-trip. Under the Pattern Day Trade
Rule, the Financial Industry Regulatory Authority (FINRA) only allows
three (3) round-trips within a five (5) rolling day9 period. This rule only
applies to margin accounts10.11
8
Volatility here refers to the tendency of the price of an asset to fluctuate.
The five rolling days here refer to five consecutive trading days.
10
Margin accounts are the accounts held by the broker that allows the market
participant to trade on credit. For instance, if the trader has deposited $45,000 in
the account, if they are trading on margin, the broker may allow the trader to take
trades up to $90,000.
11
According to the FINRA, any account that places four day trades or more, within
in a five trading day period is permanently deemed to be a ‘pattern day trading’
(PDT) account. The FINRA mandates that pattern day trading accounts maintain a
minimum daily equity balance of US $25,000. If the account balance falls below
US $25,000, traders can only perform closing transactions only until the account
balance is increased to US $25,000. The FINRA deems Non-Day Trading Account
as any account that has never placed 4 trades within a 5-day period. Non-Day
Trading Accounts are required to have an equity balance of at least US $5,000
(Trade Station 2016).
9
4
Chapter One
Traders select their trading style based upon: the size of their trading
account; their level of experience; the amount of time they are willing to
dedicate to trading; and their risk tolerance12.
1.2 Portfolio Allocation
Portfolio allocation is the process by which the market participant
decides which assets should compose the portfolio. Two factors that
influence portfolio allocation are the time horizon and risk tolerance. Time
horizon refers to the age of the investor/ trader relative to their retirement.
Generally, the longer the time horizon of an investor, the more risk their
portfolio can bear. This is due to longer time periods provide more time
for the investor to recover from losses. For example, assume an investor
made a 25% loss in a portfolio this year. If that investor has a long time
horizon, then they have several years to recover from such loss.
The risk tolerance refers to how much risk that an investor/ trader is
willing to take. Risk here is defined as the likelihood that an investment
may earn a return lower than the expected return. However, the greater the
returns from an investment deviates from its expected returns, the riskier
the investment. In fact, the Risk-Return Tradeoff asserts that the returns
from an investment can be increased by taking larger risks. Investors/
traders trying to make profits cannot eliminate all risks. Instead, they
should try to find a balance between the desired return from their
investment and the associated risks. The risk tolerance of each investor is
influenced by their personality as some investors are willing to take more
risks, with the goal of earning a profit, than others.
Risk adverse investors with short horizon would prefer portfolios
which have a high weight of income stocks13. On the other hand, investors
with a long horizon may prefer a portfolio with a higher weight of growth
12
Risk tolerance refers to how much loss a trader/ investor is willing to risk while
trading/ investing.
13
Income stocks are equities that pay regular dividends. The dividend of income
stocks often increases over time (Reilly and Brown 2011).
General Introduction
5
stocks14. Moderate investors with moderate risk tolerance and time horizon
may prefer a portfolio with a higher weight of value stocks15.
1.3 Profit Loss Ratios
Many retail traders may trade ad-hoc, or they may go to forums and
inquire about other market participants’ trades in order to mirror them.
Such traders may fear that they may lose money, subsequently influencing
their consistent search for the correct tool which can help them make
accurate trades 100% of the time. Retail traders may be searching for the
“Holy Grail”, the trading secret that would lead to instant profitability.
Such search may be unjustified since it is possible for a trader to correct
about the market direction only 50% of the time yet still be profitable.
Traders should be mindful of profit to loss ratios. If a retail trader can
successfully trade with a profit to loss ratio of at least 2:1 then they can be
profitable even if they are only accurate about the direction of the market
50% of the time.
Most traders who are unable to achieve financial success on financial
markets do so because they are trading with a profit to loss ratio where the
average size of their financial gain is less than the average size of their
financial loss. They could have a profit to loss ratio of 1:2 or even worse.
Such statistics may be a result of the retail trader holding losses too long,
or closing profitable positions too early. Throughout the course of this
book, consideration is given to various tools and analytical techniques
which could result in the retail trader earning more financial gains than
losses.
1.4 Book Objectives
Trading has the potential to general large profits in a very short period
of time. However, if an economic agent attempts to trade without first
understanding certain fundamentals about trading, they may lose large
amounts of money while trading. Moreover, they may incur losses without
understanding why.
14
Growth stocks are equities of companies whose earnings are growing above the
average market rate. Growth stocks rarely pay dividends since the companies
reinvest their earnings (Reilly and Brown 2011; Levin and Wyzalek 2014).
15
Value stocks are equities that are trading at a price that is low relative to its
fundamentals (Levin and Wyzalek 2014).
6
Chapter One
The objective of this book is to teach a potential reader, which is
lacking prior knowledge of finance, the relevant information about
financial exchanges, and how to profit from day trading. This book seeks
to provide a roadmap for the trader who desires to learn to trade from a
systematic approach rather than based on ad-hoc decisions and emotions.
A study of the guidelines presented herein will help identify and
eliminate the causes of failure, such as a poor strategy, incorrect data
interpretation, poor risk management, and improper strategy evaluation.
1.5 Outline of Book
While several types of financial instruments are available on stock
markets, this book focuses mainly on trading stocks and currencies.
Chapter Two of this book will review basic concepts in trading. It
addresses issues such as how to open an account, and how to identify
stocks to trade.
Chapter Three explores the technical tools used for trading. It reviews
market conditions, candlesticks, and chart patterns.
Chapter Four considers a number of strategies which can be used by a
trader to earn a profit. This will be supplemented by the strategies which
can be used to manage risk in Chapter Five.
Chapter Six probes into the average trading day of the market
participant, and presents a general conclusion.
1.6 Summary Insight
This chapter reviewed the basic concepts of trading. First, this chapter
makes the distinction between trading and investing. Moreover, it makes
the distinction between day trading, scalping, swing trading, and investing.
This chapter then outlines the general risk preferences of different
economic agents, and their predilection for portfolio allocation.
Chapter Two, the next chapter, investigates the basic fundamentals of
day trading.
CHAPTER TWO
DAY TRADING
2.0 Introduction
Many different economic agents enter financial markets, and may trade
financial assets with the objective of making a profit. An uninformed but
interested economic agent may be unaware of how to begin the process to
engage in day trading. This chapter outlines the process in which such
economic agent may open an account to engage in day trading. It starts by
outlining where assets are traded. Then, it explains the factors that the
economic agent should consider before opening an account. This is
followed by a review of how the economic agent may identify potential
stocks to trade; and an overview of the different analysis techniques that
the economic agent may consider.
2.1 Where Assets are Traded
Stocks and other financial securities are traded on exchanges. An
exchange is an organized market where securities, commodities,
currencies, and derivatives are traded. Exchanges with a physical location
are referred to as centralized markets or centralized exchanges. Exchanges
that do not have a physical location are referred to as over-the-counter
(OTC) markets.
The top centralized exchanges in the world on the basis of market
capitalization are the New York Stock Exchange (NYSE), the NASDAQ,
the Tokyo Stock Exchange, the London Stock Exchange, and the Shanghai
Stock Exchange. Within the Caribbean region, there are smaller
centralized exchanges such as the Eastern Caribbean Securities Exchange
(ECSE), the Barbados Stock Exchange, the Jamaica Stock Exchange, and
the Trinidad and Tobago Stock Exchange (TTSE). The smaller exchanges
tend to be less efficient than the exchanges in developed countries.
8
Chapter Two
2.1.1 The Forex Market
The trade of foreign exchange, or forex, is considered as trade in an
OTC market. This perception arises is due to the entire market being run
electronically, within a network of banks, continuously over a 24-hour
period.
The forex market is attractive for trading for a number of reasons. They
include: i) the large size of the market; ii) the high market liquidity; iii)
low transaction costs; iv) the 24-hour market; and v) low barriers to entry.
The forex market is the largest financial market in the entire world. In
fact, the market capitalization of the forex market is approximately US$6
trillion a day (Nag and McGeever 2016), while the market capitalization of
the NYSE, the largest exchange, is only US$45 billion a day (NYSE
2017). The forex market is so large that it is difficult for any one market
participant to manipulate the market. In contrast, the stocks market is often
manipulated by large participants.
The forex market is highly liquid. This is advantageous to traders as it
means that they can immediately buy or sell forex at the market price
whenever they desire. There will always be someone at the market willing
to take the other side of the trade. Thus, a trader will never be stuck in a
position for a currency pair.
A currency pair is the exchange rate or quotation for two currencies.
For example, the Euro / United States dollar (EUR/USD), the United
States dollar / Japan yen (USD/JPY), and the United Kingdom pound /
United States dollar (GBP/USD) are currency pairs. It shows how much
units of one country’s currency is traded for another country’s currency.
The major, and most actively traded currency pairs are: EUR/USD,
USD/CAD, AUD/USD, USD/JPY, GBP/USD, and USD/CHF. Several
currency pairs for developing countries are considered minor currency
pairs, or exotics.
The high liquidity and competition on the forex market results in low
spreads between bid and ask16. Such low spreads result in low transaction
costs per trade. In fact, for a trading factor of 0.01, some brokers may
16
The bid price is the price that the market participant offers to purchase the asset.
The ask is the price that the holder of an asset requests for the sale of the asset. The
retail trader can sell an asset at the bid price, but purchases assets at the ask price.
Day Trading
9
charge a commission of only US $0.09 (9 cents). In contrast to the trading
of stocks, some brokers may charge US$5 per trade.
The forex market is open 24 hours a day as a result of the overlapping
of the majour markets. The forex market has four major trading sessions:
the Sydney session; the Tokyo session; the London session; and the New
York session. Table 2.1 below outlines the time for the majour trading
sessions.
Table 2.1: Open and Close times for the Major Trading Sessions
Time Zone
Sydney Open
Sydney Close
April – October
EDT
6:00 PM
3:00 AM
GMT
10:00 PM
7:00 AM
Tokyo Open
Tokyo Close
7:00 PM
4:00 AM
11:00 PM
8:00 AM
London Open
London Close
3:00 AM
12:00 PM
7:00 AM
4:00 PM
New York Open
New York Close
8:00 AM
5:00 PM
12:00 PM
9:00 PM
Sydney Open
Sydney Close
Tokyo Open
Tokyo Close
London Open
London Close
New York Open
New York Close
October – April
4:00 PM
1:00 AM
6:00 PM
3:00 AM
3:00 AM
12:00 PM
8:00 AM
5:00 PM
9:00 PM
6:00 AM
11:00 PM
8:00 AM
8:00 AM
5:00 PM
1:00 PM
10:00 PM
There are low barriers to entry to trade on the forex market. In fact, a
retail trader17 can open an account to trade forex with as low as US$100.
However, for stocks, the minimum account size allowed by brokers is
US$500.
17
A retail trader is a market participant that engages in the practice of trading
financial assets. Throughout the course of this book, the terms “retail trader”, and
“market participant” will be used interchangeably.
10
Chapter Two
2.2 Day Trading
The objective of the day trader is to make money from small price
movements in an asset. For simplicity, consider only stocks.18 Therefore,
the day trader is trying to profit from small movements in the price of
stocks. This can be done by trading large volumes of the stock or taking
larger positions. These positions may be larger than what some economic
agents may feel comfortable investing. However, the risk is managed since
the position is held for a short period of time, a few minutes to a few
hours, and the trader monitors the prices while holding their position.
To put day trading in context, consider the following example. An
economic agent can invest $20,000 in a mutual fund19 and earn perhaps a
5% return per annum. This works out to be just $1,000. However, a day
trader could invest the same $20,000 by purchasing stocks in 1 day. If by
the end of the day, when the closed the position they made a profit of 5%,
then they would make $1,000 that day. Thus, if the economic agent
continues trading the same volume, it is possible to make a profit way in
excess of 5% in that year.
A trader can find a stock whose price can move by at least 5% within a
day. However, not all stocks in the market will experience such large price
movements. In fact, it may be only stocks that a reacting to news that may
experience such large price movements. In general, good news about a
stock, and the company’s profits should cause a positive price movement.
Contrastingly, bad news about a stock or a company’s profitability should
cause a decline in the price of stocks.
To illustrate how stocks respond to news, consider this real-life
example. On April 1, 2016, Sky Solar Holdings’ stock SKYS had a very
good performance. It increased by 88% in 1 day. Upon the examination of
news at yahoo finance, it was revealed that Sky Solar Holdings reported
18
There are many different types of assets on financial markets. For instance, there
are equities, fixed income securities, mutual funds, commodities, forex and
derivatives. However, for the purposes of this book, only stocks are considered.
19
A mutual fund is a portfolio which is managed by a fund manager. Mutual funds
are sold directly to consumers. Mutual funds are marked to market daily, allowing
their price to change on a daily basis. However, they are relatively safe
investments, allowing an economic agent to earn a modest return, while taking
minimal risks (Investopedia 2017). Since mutual funds are managed by
professionals, and individual with absolutely no knowledge of finance can safely
earn a given return.
Day Trading
11
the news of good profits for 2014 and 2015. They stated, “Q4 2015 total
revenue of $12.2 million, up 49% over Q4 2014.” (Global News Wire
2016).
A more recent example can be seen by Pokemon Go. Following the
release of Pokemon Go, Nintendo’s stock price almost doubled. On July 6,
2016, Nintendo’s stock (NTDOY) was US $17.63. By July 18, 2016,
NTDOY peaked at US $37.37, a 111% increase (Yahoo Finance, 2016).
This increase in the stock price was due to traders and investors
anticipating Nintendo earning significant profits from its 33% ownership
in the Pokemon Company, which controls the merchandising and licensing
of the Pokemon franchise, and an estimated 5-10% equity in the game’s
developer, Niantic (Colgan 2016).
In the week of the 18th to 22nd July 2016, Nintendo announced that
Pokemon Go will have only a “limited” effect on its profitability since the
game has other equity holders (Charles 2016). Since then the stock price
of Nintendo fell from US $37.37 on Monday July 18, 2016 to US $26.75
by Monday July 25, 2016, a 28% decline (Yahoo Finance 2016).
Day traders should look for stocks whose prices can move at least 5%
within one day. Given that there are thousands of stocks on stock markets,
a day trader should utilize the correct tools on the market.
Some of the tools that can be used include:
x
x
x
x
Stock Charts;
Stock Scanners;
Stock News; and
Chat Room (optional).
Stock Charts are charts that display patterns and trends of stock prices.
A trader should examine stock charts to determine which stocks should be
traded.
Stock Scanners are software that can scan the stock market to find
potential stocks of interest. For instance, if a trader is interested in stocks
that experienced at least a 5% price movement within the last 10 days, the
trader can input such requirements in the scanner and provide only the
stocks that meet the trader’s criteria.
12
Chapter Two
Stock News provides information on companies. In other words, is a
company’s stock has experienced a significant change in price, the stock
news can be used to determine the reason for the price movement.
Stock Chat rooms are private forums on the internet whereby members
may discuss various issues regarding stocks. Members of the chat room
may provide tips as to what stocks should be traded, what positions to
take, and when to close certain positions.
Each one of the aforementioned tools may cost as much as $100 a
month. While some of the services are offered free, the best services
usually incur a fee. While such costs may be discouraging to a potential
new trade, a trader should consider the act of trading as a professional
business. Like many other businesses, there is some operational costs
involved in order to maintain operations. However, if these services can
assist a trader to make well-informed decisions, and profitable trades then
the cost of such information may be justified.
In microeconomics, a firm may incur various costs in its operation.
However, it would continue to produce up to the point where its marginal
costs20 equate its marginal revenue21. In other words, once its marginal
costs of production are less than its marginal revenue, it would produce.
The firm would maximize its profit at the particular point where the
additional revenue from production just equates the additional cost of
producing.
More simply expresses, if a trader incurs these costs to make trades, it
is possible for the trade to generate profits that far exceed these costs.
A new trader, with little or no experience in trading, should first
practice paper trading before trading with real money. Ameritrade22, Trade
20
Marginal cost is the cost of producing one (1) additional unit of output.
Marginal revenue is the revenue from producing and selling one (1) additional
unit of output.
22
Ameritrade paper trading system may be accessed through Investools. This is
available via the following link
https://toolbox.investools.com/portfolio/paperMoneyLanding.iedu#.
If
users
attempt to download the program directly from Ameritrade, some traders may be
blocked as Ameritrade requires users to register but it only allow US citizens or US
residents to create accounts.
21
Day Trading
13
Station, Sure trader and Market Watch23 can be used to do this. A new
trader can open a demo account in Ameritrade and trade with imaginary
money. A new trader should also try to use free services for stock news
and charts, and try to develop a working trading strategy before trading
with real money. By doing this, the trader can eventually develop
strategies with known success rates. It is important to note, most new
traders that fail, do so because they have no proven trading strategy. In
other words, they are trading based on a guess, and they have no statistics
to show the percentage success rate of their trading strategy.
A day trader should look for stocks whose prices can change by at least
5% within a few minutes. The average stock will not experience such large
price movements within such a short period of time. Therefore, such
stocks are trading at extremes.
2.3 Opening an Account
To commence day trading, a trader must first open an account with a
broker. The trader must fill in their name, address, and other personal
information with the broker. The fees of brokers vary. Table 2.2 provides a
brief summary of the different fees of stockbrokers as of 2016.
Table 2.2: Brokers, their Commission Fees and Minimum Account Sizes
in the US
Name
Scottrade
Fee
US$7 commission per trade
ETRADE
US$9.99 commission per
trade
US7.95 commission per
trade
US$4.99 commission per
trade
Fidelity
Trade Station
23
Minimum account size
US$2,500 account
minimum.
US$500 account
minimum.
US$2,500 account
minimum.
$5,000 Minimum for
Non-Day-Trading
Account. $30,000 for a
Day Trading Account.
Market Watch account is not a real account. It is a demo which starts all players
at $50,000 and charges a commission of $7 per trade. It is very easy to create a
demo account at Market Watch. It is available at:
http://www.marketwatch.com/game/
Chapter Two
14
Speed trader
Light Speed
Sure trader
FX Choice
US$4.49 commission per
trade
US$4.00 per trade for 250
to 750 trades, plus accounts
less than US$15,000 will be
charged a US$25 monthly
minimum commission fee
US$4.95 per trade up to
1000 shares
US $0.09 per 0.01 trading
factor
US$25,000 is the
minimum initial account
size.
$500
$100
Before selecting a broker, a new trade should consider:
1. All the fees of the broker;
2. The minimum account size required by the broker; and
3. The online platform and the speed in which the broker execute
trades.
The trader should consider all fees. These include the commission fees
per trade, plus possible hidden fees. For instance, Light Speed charges a
fee of US$25 per month if the account size is less than US$15,000. Some
brokers charge a fee for inactivity. For example, Sure Trader charges
US$50 per quarter if there are less than 15 trades undertaken. Brokers
typically charge additional fees for additional services. For instance, Speed
Trade charges US$60 for international wire transfers. Some brokers have
additional rules regarding transactions. For instance, if a trader uses Sure
Trader as their broker, if the trader is using margin on Penny Stocks24, the
account of the trader may be liquidated by Sure Trader.
Consider an example where a retail trader may decide to open a daytrading account with a stockbroker. Assume that the commission per trade
is US$5, therefore the commission per round trip is US$10. If the retail
trader purchases one share of a stock at US$30 per share, the trader would
need a positive price movement of US $10, or a cumulative effect of price
movement and dividend payments of US$10 in order to break even.
However, a US$10 price change is an approximate 33% change, which is
considered large. If the trader desires to earn a profit from a smaller price
movement they would need to compensate with volume. In other words,
they will need to buy more than 1 share. For example, if the retail trader
24
Sure Trader refers to a Penny Stock as any stock below $3 (Sure Trader 2016).
Day Trading
15
bought 5 shares at US$30 each, (resulting in a total of US$150 for the long
order), then the trader would only require a positive price movement of
US$2 per share in order to break-even.
In the case of forex trading, a retail trader may seek to profit from
changes in the price interest points (pips). A pip measures the extent of
change incurred in the exchange rate for a currency pair. For example,
assume that the EUR/USD moves from 1.2250 to 1.2251. The 0.0001
change in the quotation is one pip. Alternatively expressed, a pip is
1/10,000 of a dollar.
Just like stock trading, there are multiple brokers in the forex market.
Some popular brokers include Ameritrade, Ally Invest, ATC Brokers,
Forex.com, FX Choice, and Oanda. Table 2.3 provides an overview of the
commissions and minimum account size for the aforementioned brokers.
Table 2.3: Brokers, their Commission Fees and Minimum Account Sizes
in the US
Online
Broker
FX Choice
OANDA
Ameritrade
Forex.com
Ally Invest
ATC
Brokers
Commissions
Account minimum
US$0.09 per trading factor of
0.01
Both spread markup and
commission ($50 per one million
units)
Both spread markup and
commission ($1 minimum;
$0.10/1,000 units per side),
depending on currency.
Spread markup
Spread markup
$100
$1 per 10,000 units, round turn
$0
$0
$50
$500 ($3,000
recommended to trade
full range of products)
$3,000
Source: Adapted from O'Shea and Royal (2018)
FX Choice has a relatively cheap and simple commission system. FX
Choice charges a commission of US$0.09 per trading factor. Additionally,
this commission is only charged when an order is closed. So for a trading
factor of 0.05, the commission would be US$0.45, for a trading factor of
16
Chapter Two
0.20 the commission would be US$1.80 and so on. Subsequently, even if
the gain per dollar is a few cents, a retail trader can earn a profit from
trading forex. Thus, a retail trader that is trading forex can operate a
smaller account and be profitable than a retail trader that is trading stocks.
It is noteworthy that the spreads for major currency pairs during
normal trading periods on weekdays, (for e.g. at 9:30 am on a Monday)
tend to range from 7 pips to 9 pips. Given the cost of commission of
US$0.09 per trading factor of 0.01, a retail trader’s order would need to be
in the correct position by 16 to 18 pips in order to break-even on a trade.
The minimum account size is also important since if a trader does not
have the minimum account requirements, they cannot use that broker to
trade. For example, Fidelity minimum account size is US$2,500 for the
trade of stocks. Whereas for forex trade, FX Choice minimum account size
is US$100. Given the small account size mandatory requirement, and the
small, yet proportional rate for the charging of commission, it is relatively
easier for a retail trader to enter the forex market than the stock market.
An important consideration is the requirements by the FINRA. Recall,
FINRA mandates that pattern day trading accounts maintain a minimum
equity of US$25,000, while non-pattern day trading accounts maintain a
minimum equity of US$25,000. Since most day traders will undertake
more than 3 round-trips within 5 consecutive trading days, then they will
need to have an account balance in excess of US$25,000 in order to
actively trade. However, Sure Trader, a broker based in Nassau, Bahamas,
do not enforce the PDT restrictions of the FINRA. Subsequently, a trader
with less than $25,000 may actively trade stocks on Sure Trader.
It is important to note the disparity in the financial requirements for
trading stocks and trading forex. For example, using a trading factor of
0.01, if there is a positive price movement by 118 pips (US 11.8 cents), a
retail trader can generate a profit of US$1. In terms of the risk of that
trade, then if there was a movement of 100 pips in the wrong direction the
trader would stand to lose US$1.18. However, in the case of stocks, a
trader buying 5 shares at US$30 each and hoping for a US$2 price
increase would risk US$150 just to break-even.
The online platform of a broker is also a factor to consider for trades.
In the United States (US) and most exchanges in developed countries, the
broker would provide an online platform that allows a trader to execute
trades immediately. However, in exchanges in developing countries, there
Day Trading
17
may be no online platform. This is the case for brokers operating in the
TTSE.
The absence of an online platform, offered by brokers in a country,
results in inefficiency in the exchange. In order to make a trade, a trader
would most likely be required to go physically to the broker, fill out some
forms, and exchange cash in order to make an order. Such conditions may
result in little price movement in the stock market. In fact, for some stocks,
there may be absolutely no trades and no price movement on some days.
Inefficient markets may have wide spreads between the bid and ask.
This may be problematic for a trader that desires to liquidate a large
proportion of their assets suddenly, as they may be unable to acquire a
buyer for their assets. This may result in the trader accepting a lower price
than they desire for their assets.
In stock exchanges in developed countries, there are typically Market
Makers to facilitate liquidity in the market. Market Markers buy and sell
assets, even when no one else is willing to trade the asset. In developing
countries, there may not be a Market Maker on the exchange.
It is important to note, all brokers will ask the account holder for the
following information to create an account:
x
x
x
x
x
Contact Email address;
2 Valid photo IDs (driver’s license, national ID, passport);
Bank account information;
Employer’s address and telephone number; and
Financial information (annual income, and total net worth).
Some brokers have additional requirements for opening account. For
instance, Sure Trader requires:
x Financial and professional references;
x Proof of residency (e.g. a utility bill, or bank statement, etc. no
older than 6 months, with the account holder’s address); and
x Non-US individuals are required to submit a W-8BEN form, NONUS Entities are required to submit a W-8BEN-E form, and for
accounts that will be comprised of both non-US entities and
individuals, will be required to submit a W-9 form.
Chapter Two
18
2.4 Important Questions to Consider Before Trading
Before trading in any market, a trader should consider the following
questions:
x What types of financial markets are being considered for trading?
x What is the trading strategy?
o How are stocks selected?
o What setups and scanners are used?
o What strategy should be used? e.g. price crossover strategy; or a
reversal trading strategy.
o What are the statistics from paper trading on their strategy?
o The time of day the trade was executed. What are the results of
such trades?
x What is the strategy for managing risk?
o What is the profit-loss ratio?
o What is the max loss ever experienced?
o How frequently are losses made? What is the empirical
probability of making losses?
As previously mentioned, stock markets facilitate the trade of stocks,
while forex markets facilities the trade of currency pairs. In stock markets,
a retail trader needs to analyze and consider the dynamics of the stock
market to inform their trades. The trader makes a profit from selling stocks
at a price that is both higher than the purchase price of the stock and the
cost of the commission to the broker.
In the case of forex markets, a retail trader should focus their analysis
on currency pairs and the factors affecting them to inform their trades. The
forex market is advantageous and it allows retail traders with small
accounts to trade on margin and earn profits from changes in pips. A pip is
the smallest measure of change in a currency pair in the forex market. For
instance, assume the price of a currency pair moved from US$1.259 to
US$1.260. The change in price was US$0.001 or 1 pip.25 Brokers allow
forex traders to place trading factors that are related to pips. A trading
factor is analogous to a betting scale to determine how much of a retail
trader’s capital is risked per trade. For example, at a trading factor of 0.01,
a very small percentage of the retail trader’s account is risked with the
trade. In fact, at a trading factor of 0.01, if a trade is in the correct position
for 10 pips it would only result in a profit of 10 cents. However, if the
25
A pip is also 1/1000 of a dollar.
Day Trading
19
trading factor was 0.10, a trade is in the correct position for 10 pips would
have resulted in a profit of US$1. Likewise, at a trading factor of 1.00, a
trade in the correct position of only 10 pips would have resulted in a profit
of US$10. It is noteworthy that while increasing the trading factor can
increase the payout of each correct trade, it can also increase the loss of
incorrect trade. Thus, traders need to mindful of how much capital they are
risking with each trading factor if they don’t want to quickly diminish their
account.
While paper trading, new traders should document their strategies
used, the times they were executed, and the profits made. Traders should
document the actual ratio of profit to loss. As previously mentioned, an
acceptable profit-loss ratio would be a 2:1 ratio or higher. In other words,
even if the chosen strategy results in a trader earning a profit 50% of the
time, and losing 50% of the time, the strategy would still be acceptable.
Moreover, a higher profit to loss ratio implies that a trader can be wrong a
lot, yet still make a lot of money.
Retail traders also need to consider how they make decisions based on
real time. Markets can move fast, and if a trader is slow in performing
analysis, it is possible for them to miss profitable opportunities. Traders
should also practice paper trading so they may become familiar with the
trading platform of the broker. Experienced traders, can also practice paper
trading so they may practice new strategies.
Retail traders also need a strategy to manage their risks and losses. For
instance, suppose the market moves in an unexpected unfavorable
direction. The trader should have a limit on much loss they are willing to
accept before they close the position. For example, if while holding an
asset in the long position, the price of the asset declines unexpectedly by
30 cents, then the trader may decide to close the position in order to
prevent the loss from growing.
Retail traders need to manage their risk. For example, suppose a trader
won 15 consecutive times, however, each time they won, they invested all
of their earnings in the next trade. Then, whenever they incur the losing
trade, they risk losing all their gains. In such instance, the trader would
have a 15/16 (94% success rate), but the one time they lost, they risk
losing all their earnings because they failed to properly manage their risks.
Traders should only trade with real money when they have a strategy
that has been proven to be profitable.
Chapter Two
20
2.4.1 Types of Orders
While paper trading, the trader will have to make orders for stocks. A
trade order is an instruction from a trader/ investor to a broker to enter or
exit a position. Trades can be entered in different directions. Long orders
refer to orders to purchase an asset. Short orders are orders to sell an asset.
The direction of the order issued by the trader depends on their
expectations of the market. If they expect the price of an asset to rise, they
may issue long orders and they plan to buy the asset and resell at a higher
price. If they are holding stocks and anticipate a decline in its price, they
may issue a short order. If they anticipate a decline in the stock price but
they don’t own the stock, they may issue a short order to short sell the
stock.
There are different types of orders, they include:
x
x
x
x
x
Market;
Limit;
Stop;
Conditional; and
Duration.
A market order is an instruction to a broker to long or sell the asset at
the market price. For instance, if the trader issues a long market order, then
the broker will purchase the asset for the trader at the ask price26. Market
orders tend to be filled immediately. However, the disadvantage of market
orders is that they do not guarantee a price for the order to be filled. There
can be slippage in price as market orders are filled. For example, assume a
trader issued a market order to short 1,000 shares of a stock that they
owned. This order is only filled by the broker finding other traders willing
to purchase the stock. The first purchase order might be an order to
purchase 500 shares at a price of US$20. Then, there may be a second
order to purchase 300 shares at $19 per share. Then there might be a final
order to purchase 200 shares at $18 per share. Although all 1,000 shares
are sold, the average price the trader received was $19.3 per share.27
26
The ask price is the price the seller is asking for the asset. The ask price is
distinct from the bid price. The bid price is the price the buyer is offering to pay for
the asset.
27
($20 x 500/1000)+(19 x 300/1000)+(18 x 200/1000) = 19.3
Day Trading
21
Due to the potential limitation of slippage, some traders may issue
limit orders. Limit orders are orders which specify how much volume of
an asset should be traded and at what price. Unlike a market order in
which the trader sells a specified volume at the prevailing market price, in
a limit order, the trader must specify the quantity of the asset that must be
sold at a specific price. Traders use limit orders to protect themselves from
sudden adverse movements in price. For example, a trader may issue a
limit order to purchase 1,000 shares at $20. That guarantees all the shares
purchased will be the same price. When the stock price rises to $26, the
trader may issue a limit order to sell 1,000 shares at or above $26.
However, the trader may issue a limit order to sell 1,000 shares if the stock
price moves to $25.
A stop order is an order to long or short assets only when they reach a
particular price. Long stop orders are placed above the current market
price, while short-stop orders are placed below the current market price.
Once the asset’s price reaches the stop level, the order is automatically
transformed to a market or limit order. Subsequently, stop orders are either
stop market order or stop limit orders.
A stop market order transforms into a market order once the stop level
has been reached. Likewise, a stop limit order converts into a limit order
once the stop level is reached. It is plausible to question, why would any
economic agent want a stop order to purchase assets at prices above the
current market price. However, a trader may issue a stop long order to
purchase assets if they rise above a certain price. The trader may specify
the stop price at a resistance price. Then once prices break resistance, it
suggests that the market is becoming bullish, and subsequently, the trader
could ride the trend. Likewise, in the case of a short-stop order, if stop
price is at or below support, then once the stop price arrives, the market
would have broken support. The trader could then ride the bearish trend to
make a profit.
Another application of stop orders can be seen with trailing stops. A
trailing stop is a special stop order in which the stop limit is a percentage
away from the current market price. The objective of any trader using a
trailing stop is to protect gains. Trailing stops allow for a position to
remain open when the prices are moving in the correct direction, but close
if the price changes in the adverse direction by a particular percentage.
A trailing stop can be explained by the following example. Assume a
trader went long and bought a stock for $50, and placed a 15% trailing
22
Chapter Two
stop order. Assume the stock price continues increasing. Then the order
remains open. However, after peaking at $80, the stock price suddenly
declines by 15% to $68. Then, at $68 the stop order will be activated to
close the position.
A trailing stop automatically tracks the asset’s price and does not have
to be manually reset as in stop orders. Consider another example. Assume
a trader decided to short sell an asset at $40 and placed a 5% trailing stop
order to close the position. Assume the price of the asset declined by 10%
to $36, then increased by 5% to $37.8. At $37.8, the stop order will
activate and close the position.
Conditional orders are orders that are automatically canceled or
submitted if specific conditions are met. The main types of conditional
orders are: order-cancel-order (OCO) and order-send-order (OSO). In
OCO, a trader may enter multiple orders simultaneously. However,
whenever one order is completely filled, the remaining orders are
automatically canceled. An OSO is a primary order that will multiple
secondary orders once the primary order is filled.
Duration orders are orders that specify the duration of time in which an
order remains on the market until it is canceled. The platform of the broker
will determine duration times for orders. The duration can range from a
few minutes to a day. Some brokers allow longer durations.
2.4.2 Level 1 and Level 2 data
Once a trader has set up an account with the broker of their choice,
they may proceed to the online platform to make an order. In the platform
there should be:
x A Market Depth (Level2) window;
x A Time and Sales window; and
x An Order Entry window.
Some brokers may provide the three (3) aforementioned tools in the
same window. Other brokers will provide the tools in separate windows.
The Market Depth window displays the Level 1 prices. Level 1
indicates the bid and the ask price for an asset. It is also referred to as the
National Best Bid and Best Offer (NBBO). However, level 1 data reveals
on the surface of the market as it ignores trading volume. Level 2 data
Day Trading
23
shows the number of buyers associated with the bid price, and the number
of sellers associated with the ask price. Traders are typically interested in
Level 2 data as it indicates the demand and associated with their respective
bid and ask prices.
For instance, the Level 1 may show that the ask price for a stock is
$20, while the bid price is $18. All a trader can discern from such Level 1
data is a $2 bid-ask spread. Upon inspection of Level 2, a trader may see
that there are 50 people corresponding to the ask price, but there may only
be 10 people that associated with the $18 bid price. In such a situation, the
supply exceeds the demand. The free market economics would result in
the price of the asset eventually decreasing closer to the bid price than the
ask price.
In addition to seeing the current amount of buyers and sellers at the
current bid and ask price, Level 2 data also displays the number of buyers
bidding below the current bid price, and the number of sellers above the
current ask price.
Level 2 data is very useful. It can indicate when a strong price trend is
nearing its end, as its demand becomes weak. Or when a breakout28 is
about to occur as demand for a stock significantly exceeds supply.
However, Level 2 tricks can help large traders deceive smaller and more
naïve traders. For instance, they can hide their order sizes by placing a
series of small orders to prevent the tip-off of other traders. Alternatively,
or conceal their actions through Electronic Communication Networks
(ECN)29. By another token, market participants can engage in spoofing30
and manipulate the market by placing large orders to give a false sense of
market direction.
Due to the risk of Level 2 data, traders should perform additional
analysis to determine if to long or short an asset.
28
Here, breakout means strong price action. It means a new uptrend or down trend.
Breakouts will be discussed later in Chapter 3.
29
An ECN is a computerised system which obtains information on the best
available bid and ask quotes from multiple market participants. It then matches and
execute orders without going through a middleman. Orders placed on ECNs are
typically limit orders (Investopedia 2017).
30
Spoofing is where large traders place large orders with the intent of sending false
direction to manipulate the market.
Chapter Two
24
The time and sales window display the transactions that occurred. It
shows the number of time, the price and the number of shares that were
traded when transactions were executed. The time and sales window can
be used to support the Level 2 data.
There is also a window to enter trades. This is where a market
participant makes their order. The trader places the market or limit order in
the trades window. Some traders may utilize hotkeys31 when entering
trades. Hotkeys are relevant since the stock market is very volatile, and
stock prices have been known to change their value by 100% or more in a
few minutes. Thus, hotkeys allow traders to execute quick commands in
order for a trader to capitalize on the quick price movements.
2.5 How to Find Stocks to Trade
Some new traders choose stock by identifying the stocks of popular
companies that they like, then entering a trade. However, it is highly
unlikely that popular stocks will make large price movements in excess of
10% is a few minutes within a day. Stocks making such large price moves
would typically be stocks that are under the radar and being influenced by
news.
Day traders typically focus on stocks which will experience high
volume trade and large price movements due to news. There is a catalyst32
which is responsible for the stocks trading on high volume and prices.
In order to find the stocks with the desired criteria, stock scanners can
be used. Some free stocks scanners include:
1. Finviz;
2. Google Finance;
3. Yahoo Finance;
4. Market Watch;
5. Stock Twits; and
6. Trade Ideas.
31
A hot key is a key on a key board that allows a trade to execute a given
command in the order window. They allow a trader to enter trades, exit trades,
trade a percentage of their stocks, place limit orders, and cancel orders. The broker
online platform might come with default hot keys to enter and exit trades.
32
The catalyst is an event, or something reported in the news which motivates
traders to trade the stock.
Day Trading
25
2.5.1 Stock Scanners
Finviz is a very user-friendly interface. On the home page, it will
immediately present the stocks with the largest price movements. A user
can search for specific stocks by their ticker, see their chart information,
and review news regarding a stock. A user can also get information
regarding the firm's Price Earnings (P/E) ratio, market capitalization, float,
price and price change, sector, etc. The charts on Finviz are very useful as
they utilize multiple moving averages and candlesticks. A trader can easily
identify resistance, support, bearish and bullish trends based upon the chart
information. If a trader pays US $24.96 a month, they can gain access to
Finviz intraday charts.33
Google Finance has an interactive filter which can be used to stock
stocks based on the criteria of the trader. Some of the criteria indicators
include P/E ratio, market capitalization, and dividend yield. A trader can
also customize their search and include other criteria pertaining to
company valuation, dividends, financial ratios, operational metrics, stock
metrics, etc. Google Finance can also be used to obtain news regarding
stocks.
Yahoo Finance is also an excellent free stock scanner. A trader can sort
stocks by largest price gainer and losers, and largest movers. Yahoo
finance provides historical daily prices on stocks, fixed income securities,
currencies, benchmark indices, commodities, and mutual funds. Yahoo
finance can also be used to access news regarding these financial assets. A
user can also create a portfolio on Yahoo Finance, which may be used to
keep track of specific assets.
Market Watch provides an excellent, easy to use, stock scanner. It can
filter stocks on the basis of price, volume, P/E ratio, and market
capitalization. The scanner can also filter stocks outperforming their 50day or 200-day moving averages, those outperforming a market index, and
those traded on specific exchanges.
Stock Twits can be used to both review historical stock prices and
news regarding companies. Users of Stock Twits also post blogs about
stock prices, their behavior, the reason for the price behavior, and potential
future price movements.
33
The tools section will elaborate upon the different tools used to help make an
informed decision regarding a trade.
26
Chapter Two
Some analysts will use multiple stock scanners to identify stocks. For
instance, some people might use Yahoo Finance to first identify stocks that
are experiencing high price movement, then they will use Finviz to see the
daily stock charts.
Apart from stock scanners, traders can also identify possible stocks to
trade by reviewing stock news. In fact, a good time to trade is after reading
the economic calendar.34 Another good time to trade is during the
reporting season. Bloomberg earning announcements35 will state when
specific companies listed on the stock exchange will report their earnings.
Consequently, a trader may visit Bloomberg, identify when the companies
will report earnings and include these stocks in their watch-list. The trader
may take a long position if good news is reported, and a short position if
bad news regarding a company and its management is reported.
Trade Ideas is a very good stock scanner. It allows traders to find
patterns in real-time. Upon logging in, a trader can choose from a range of
pre-configured scanning settings to identify stocks with bearish, bullish, or
neutral trends. For example, if a trader is looking for stocks that are
exhibiting a bull flag pattern, a trader can set the scanner to search for
stocks that experienced a 5% price increase within the last hour, and the
price has been fluctuating by 1% within the last 15 minutes. Or, a trader
with a small account can search for stocks priced between $3 and $15. Or
a trader can search for stocks with a market capitalization no greater than
$100 million, and experience a 5% increase within the last 50 minutes. Or
a trader can use the scanner before the market opens to find stocks with a
low float36 and at least 10% of the float with pre-market orders. There is
no limit to the different combinations of the stock scanner settings that a
trader may employ.
Trade Ideas provide chart windows, alert windows which stream and
display events as they happen in real-time based on the filters selected.
Trade Ideas also has an Odds Marker which uses probability to test
inputted strategies in real time. Trade Ideas also has a free chat room.
34
Although the economic calendar is not a stock scanner, it provides excellent
news about companies.
35
See http://www.bloomberg.com/apps/ecal?c=US
36
For the purposes of this book, low float stocks refer to stocks with 10 million or
less in total share. Low float stocks typically refer to stocks with a relative small
number of shares available for trade. Low float stocks have been identified as a
preference for trade since it supply is limited, increases in demand may result in
large changes in price.
Day Trading
27
Participants in the chat room may discuss trading strategies and potential
assets to trade. While, Trade Ideas may cost US $99 per month, its
services can be very valuable for an active day trader.
Trade Ideas is recommended to any trader considering day trading with
real money. However, for traders practicing with paper money, they may
use free filters such as Finviz, Google Finance, and Yahoo Finance, as
they seek to minimize their costs while learning how to trade.
2.6 Creating a Watch-List
Day traders seek to trade stocks that are experiencing relatively high
price movements. Such stocks may be trading in high volume and
responding to news. Before purchasing any stock, it advisable for a trader
to create a watch-list37. In fact, the trader may use stocks scanners to assist
in their creation of a watch-list of a few stocks, and then apply analysis to
the stocks to determine the correct entry position.
There are several methods in which a watch-list may be systematically
created. Some methods include:
x Top-Down Analysis;
x Fundamental Analysis; and
x Technical Analysis.
2.6.1 Top-Down Analysis
Top-Down Analysis refers to the technique whereby investors/ traders
first consider searching for assets from broad categories, and then they
gradually narrow down their search parameters. For example, an investor/
trader can begin by searching markets, then sectors, then industries, and
finally individual companies.
Top-Down Analysis is based on the premise that strong markets are
comprised of companies with strong performing stocks. Subsequently, an
investor/ trader can start exploring an industry and eventually filter out the
strong companies.
In Top-Down Analysis, an investor/ trader can begin by studying
markets. Benchmark indices can be used to analyze markets. For example,
37
A watch-list is a list of stocks that a trader is considering buying or selling.
28
Chapter Two
a trader may review the Standard and Poor’s (S&P) 500 Index38 to get
insights about the general performance of stocks in the US.
Because an entire market can be difficult to track, investors often use
market indices as a benchmark for a market’s performance. For example,
the U.S. stock market is commonly tracked by the Standard and Poor’s
(S&P) 500® Index—an index comprised of 500 large U.S. companies.
Other common indices are the Russell 200039, and the Dow Jones
Industrial Average40.
Markets can be disaggregated into sectors, for instance: the energy, the
health, and the information technology sectors. Sectors can be further
disaggregated into industries. For example, the health industry can be
disaggregated into the pharmaceuticals industry, hospitals industry,
residential care facilities industry, medical devices industry, etc.
Finally, the trader can move from industries to considering individual
stocks of companies. Traders can also perform bottom-up analysis. This is
where they may begin with precise criteria for their stocks, they start with
a small pool of stocks and analyze their performance relative to their
industry, sector, and market.
Top-Down Analysis is relevant for the trading of commodities, futures,
stocks, and options.
2.6.2 Fundamental Analysis
In Fundamental Analysis, a trader/ investor reviews the financial
statements of a company to assess their financial strength and growth
potential. Investors try to find companies with strong financial
performance and growth potential
In Fundamental Analysis, the trader is trying to determine:
38
The S&P 500 index reviews the performance of the 500 largest companies in the
US.
39
The Russell 2000 index measures the performance of 2,000 small-cap companies
that comprise the Russel 3000 index. The Russel 3000 index measure the
performance of the largest traded stocks in the US, and is used as a benchmark of
the performance of the entire US market.
40
The Dow measures the performance of the 30 most traded stocks on the New
York Stock Exchange and the Nasdaq.
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29
x Are the revenues of the company growing?
x Is the company making profits? Are such profits/ loss growing?
x Is the company performing better than other competitors in the
industry?
x Can the company repay its debts?
The investor would be interested in information reported in balance
sheets, income statements, and cash flow statements. From the balance
sheet, an investor can compute a wide range of ratio. Some of the more
popular ratios include the Quick Ratio41, the Current Ratio42, the
Debt/Equity Ratio43, the Days Sales Outstanding (DSO)44, the Days
Inventory Outstanding (DIO)45, the Days Payable Outstanding (DPO)46,
the Cash Conversion Cycle47, and Inventory Turnover Ratios48.
The Quick Ratio and the Current Ratio are Debt Ratios. The Quick
Ratio measures a firm’s ability to cover its short-term debt obligations
with its most liquid assets (like cash). The Current Ratio measure a firm’s
ability to meet is short-term debt obligations with all its current assets.
The Debt/Equity Ratio shows how a firm has financed its business
operations. Generally, investors would be un-attracted to firms with high
debt-to-equity ratios as it signals that the firm may have problems
repaying their debt in the long run.
The DSO, the DIO, and the DPO are all activity ratios measuring how
effective a firm has been in converting its inventory into cash. The DSO
shows how fast a firm is able to recover its accounts receivable. Firms
with low DSOs recover their cash from accounts receivable quickly, while
firms with high DSOs take a longer time to recover their cash from
accounts receivable.
41
Quick Ratio = (Current Assets – Inventories) / Current Liabilities. Here assets
refer to the things that have a monetary value that a company owns. Liabilities
refer to things that companies use, have a monetary value, but the company do not
own.
42
Current Ratio = Current Assets / Current Liabilities
43
Total Debt/Equity Ratio = Total Liabilities / Shareholders Equity. Note, there are
also long term and short term Debt/ Equity Ratios.
44
The DSO = (Accounts Receivables / Revenue) x 365.
45
Days Inventory Outstanding = (Inventory / Cost of goods sold) x 365
46
Days Payable Outstanding = (Accounts Payable / Costs of goods sold) x 365
47
Cash Conversion Cycle = DIO + DSO – DPO
48
Inventory Turnover = Cost of goods sold / Average of Inventory
Chapter Two
30
The DIO is a measurement of the average number of days a firm holds
its inventory before selling it. The DPO shows the period of time a firm
takes to repay its creditors for their factor inputs. The summation of the
DSO, the DIO, and the DPO produces the Cash Conversion Cycle. It is a
measure of the overall effectiveness of a company in converting factor
inputs into cash.
The Inventory Turnover Ratio measures the effectiveness of a
company in selling goods. The lower the Inventory Turnover Ratio, the
faster a company’s inventory is converted into sales.
The Cash Flow Statement can be used to determine if a company has
difficulty in covering its short-term financial objectives. The statement of
cash flows can be used to compute a range of financial ratios such as the
Operating Cash Flow/ Net Sales ratio; the Free Cash Flow/Operating Cash
Flow Ratio, the Short Term Debt Coverage Ratio, and the Dividend
Payout Ratio.
Out of all the Cash Flow Statement ratios, the Dividend Payout Ratio
is of the most interest to investors. It is given by the equation
The ‫ ݋݅ݐܴܽݐݑ݋ݕܽܲ݀݊݁݀݅ݒ݅ܦ‬ൌ ௗ௜௩௜ௗ௘௡ௗ௦௣௘௥௦௛௔௥௘
௘௔௥௡௜௡௚௦௣௘௥௦௛௔௥௘
(2.01)
This ratio is an indicator of the sustainability of dividends payments.
Many investors are attracted to high dividends but will be disappointed if
dividends dwindle in the future. Moreover, if dividends payments decline
in the future, then there will be a high chance that the company’s stock
price would decline. Furthermore, since dividends are paid in cash rather
than in accounts receivable, investors may consider comparing the
Dividends Payment Ratio of a company to its available cash to ensure its
dividend payments are sustainable.
The Income Statement can be used to assess the profitability of a firm.
Thus an investor will be concerned with the revenues, costs, gross profits,
net profits of the firm. The investor can extract information to compute
certain ratios such as the gross margin, operating margin, earnings per
share (EPS) and price-earnings (P/E) ratio.
The EPS is given by
‫ ݁ݎ݄ܽݏݎ݁݌ݏ݃݊݅݊ݎܽܧ‬ൌ
௘௔௥௡௜௡௚௦௔௙௧௘௥௜௡௧௘௥௘௦௧௔௡ௗ௧௔௫௘௦
௧௢௧௔௟௡௨௠௕௘௥௢௙௦௛௔௥௘௦௢௨௧௦௧௔௡ௗ௜௡௚
(2.02)
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31
The P/E ratio is given by
ܲȀ‫ ݋݅ݐܽݎܧ‬ൌ ௦௧௢௖௞௣௥௜௖௘
ா௉ௌ
(2.03)
The Gross Margin is derived by dividing gross profit by net sales. The
gross profit margin indicates how much money is available for
reinvestment in the business after accounting for the cost of goods sold.
Operating Margin is computed by dividing operating income by net
sales. Operating margin indicates how much income is available after
coveting paying variable costs such as wages and raw materials.
The EPS is computed by dividing the net profit after interest and tax of
the firm by the total number of shares. It provides insight as to how much
earnings or profit goes to each shareholder of the company. Investors
would prefer companies with higher or growing EPS can it suggests that
the company average profits per shareholder increases over time.
The P/E is the stock price divided by the EPS. The P/E ratio is a
valuation ratio that provides an idea about the worth of a company. It also
indicates how much money an investor must pay in order to receive $1 of
annual earnings. For example, A P/E ratio of 50 means that investors are
paying $50 in order to earn each $1 of investment. The EPS and P/E ratios
are two popular financial ratios investors consider while investing.
In the performance of Fundamental Analysis, the trader/ investor must
also consider the larger economy. This is due to industry trends having a
tendency to affect the profitability of firms. For instance, as a result of the
shale revolution, and the oversupply of crude oil in the world market
between 2014 and 2016, oil prices collapsed from the US $100 per barrel
(bbl) range to the US $30 per bbl range. Consequently, firms in the crude
oil industry would experience a decline in profitability. Indirectly, this
would affect the service companies in the upstream oil industry as there
would be an eventual decline in service requests from upstream oil
companies. Thus the revenue and associated profitability of upstream
service companies would decline due to a problem arising in the industry.
It is important to note, Fundamental Analysis is relevant for stocks. It
is not relevant for commodities, or forex.
32
Chapter Two
2.6.3 Technical Analysis
Technical Analysis involves the study of the historical price of a stock
as well as its volume. Price charts are used for technical analysis. Unlike
Fundamental Analysis, Technical Analysis assumes that stock prices
illustrate adequate information.
Technical Analysis applies the principles of demand and supply to
explain asset prices. For instance, an increase in the demand for stocks
relative to their supply should lead to an increase in stock prices. Likewise,
increase in the availability of the supply of a particular stock can lead to a
reduction in the stock price. Note, Technical Analysis is relevant for
stocks, commodities, forex, futures, and options. Technical Analysis can
also be used to identify trends in asset prices. Various tools are used to
confirm trends and forecast future trends. Once the market participant
believes they have identified particular trends they can then develop a
strategy to make a profit. Chapter Three will explore Technical Analysis
and its corresponding tools in greater detail.
2.7 Summary Insight
This chapter provided an introduction to day trading. New traders are
encouraged to first create a paper account and trade with demo money
before live trading with real money. In this way, they can trade when they
are sure they have developed a strategy that has proven to be effective.
New traders are encouraged to use free stock scanners such as Finviz
and Yahoo Finance to identify potential stocks. However, Trade Ideas is
recommended for traders utilizing live money as it can easily filter stocks
by a wide range of both financial and technical criteria.
Investors and traders can use multiple methods to identify stocks. In
summary, the main methods include top-down analysis; fundamental
analysis; and technical analysis. Each type of analysis has its strengths and
weaknesses. However, this book will focus more on technical analysis as it
is used heavily by traders and investors. Chapter Three will delve into
technical tools and technical analysis in greater detail.
CHAPTER THREE
TECHNICAL TOOLS AND TECHNICAL
ANALYSIS
3.0 Introduction
As previously mentioned in Chapter Two, economic agents may use
three general techniques to create their watch-list. While Top-Down
Analysis, and Fundamental Analysis can be useful for trading, this book
focuses upon Technical Analysis. Top-Down Analysis, and Fundamental
Analysis are more relevant for long-term decision making and investing.
In trades, which may take place in less than a minute, the economic agent
may not have sufficient time to perform Top-Down Analysis, and
Fundamental Analysis. However, the univariate time series of an asset’s
price may be sufficient for quick decision making.
This chapter will explore Technical Analysis in greater detail. It
considers important technical tools, namely: candlesticks, chart patterns,
and oscillators.
3.1 Technical Analysis
Technical Analysis can be disaggregated into two categories: the
analysis of charts; and the analysis of indicators. Charts analysis involves
the utilization of charts to analyze trends in stock prices. Indicators are
essentially indices that can be used to analyze prices, volume, and
volatility.
Several types of charts can use used for analysis. Line charts, bar
charts, and candlestick charts can all be used to analyze stock price
patterns. However, the most powerful type of charts which can be used in
trading is the candlestick charts.
34
Chapter Three
3.2 Candlesticks
A candlestick is a chart that reflects the open price, closing price,
highest price and lowest price of a stock, over a period.49 Figure 3.01
provides an illustration of a candlestick.
Figure 3.01: Candlestick
Source: Adapted from Nison (2001)
The area in the candlestick between the open and the close price is
referred to as the body. The lines extending above and below the body are
referred to as shadows, wicks or tails. The shadow above the body is
referred to as the upper body, while the shadow below the body is referred
to as the lower shadow. If the stock closes at a price higher than the open
price the body is colored white. If the stock closes at a price lower than the
open price, the body is colored black. Candlesticks with longer bodies
experienced more volume and price movement than candles with shorter
bodies (Nison 2001).
Many traders prefer candlestick charts to bar charts as candlestick
charts display easy to decipher financial information. By viewing a
candlestick a trader can easily see the open prices, closing prices, and
possible patterns. For instance, if there are consecutive while candlesticks
then it suggests buying pressure and possible bullish price movements. If
49
For daily charts, each candlestick represents the price movement taking place
within a day. For intra-day charts, each candlestick can represent the time interval,
e.g. 1 minute or 5 minute.
Technical Tools and Technical Analysis
35
there are consecutive black candlesticks, it suggests selling pressure and
possible bearish price movements. See Figure 3.02.
Figure 3.02: Candle Stick Chart vs a Bar Chart
Source: Stock Charts (2016)
Candlesticks with long white bodies suggest strong buying power.
Whereas candlesticks with long black bodies suggest strong selling
pressure. Candlesticks with long upper and lower shadows suggest that
there were outliers or extremes in the prices within the trading period
(Morris 2006).
Candlesticks with long upper shadows and short lower shadows
suggest that within the trading period, pricing moved significantly above
the open price suggesting strong buying pressure within the trading period.
However, there was some volatility in the prices resulting in the stock
eventually closing at a price lower than the highest price within the trading
period (Nison 2001).
36
Chapter Three
Candlesticks with long lower shadows and short upper shadows
suggest that within the trading period there was strong selling pressure
resulting in the decline in the stock prices. However, some buying pressure
resurfaced by the time the stock was ready to close resulting in the stock
closing at a price higher than the lowest price. Figure 3.03 displays
candlesticks with long and short shadows (Nison 2001).
Figure 3.03: Candlesticks with long and short shadows
Source: Adapted from Stock Charts (2016)
Candlesticks possessing long upper and lower shadows, and short body
are referred to as spinning tops. Spinning tops are neutral candlesticks and
represent relative indecision within the trading period. In other words,
there was almost equivalent buying and selling pressure during the period,
causing the closing price to be very close to the open price (Morris 2006).
Figure 3.04 illustrates two Spinning Top Candlesticks.
Technical Tools and Technical Analysis
37
Figure 3.04: Spinning Top
Source: Adapted from Stock Charts (2016)
Another type of neutral candlestick is a Doji. A doji is a candlestick in
which the open price is almost equivalent to the close price. The length of
the shadows of doji can vary resulting in the Doji appearing like a cross,
and inverted cross, or a symmetric cross. Doji are very important in
analysis, since they may suggest a turning point in trends (Morris 2006).
Figure 3.05 displays different doji.
Figure 3.05: Doji
Source: Adapted from Stock Charts (2016)
The criteria for confirming a doji can vary based upon the price of the
asset. For example, a stock that was trading at $25 could have a doji with
only a 1/8 price difference between the open and close price. However,
another stock that typically trades in the $300 price range could form a
doji with a 1 ¼ point differential between the open and the close price. To
Chapter Three
38
confirm doji, a trader must consider the position of the doji relative to
other candlesticks. For example, a doji that occurs among other candlesticks
with small bodies may not be considered significant. However, a
candlestick with a very small body that forms among other candlesticks
with large bodies may be considered significant (Nison 2001).
3.2.1 Heikin-Ashi Candlestick
Heikin-Ashi candlesticks visually appear similar to candlesticks.
However, the prices on the Heikin-Ashi candlestick are computed
differently. In fact, the prices of a Heikin-Ashi candlestick are computed
from the price of the previous ordinary candlestick.
x Open price: is the average of the open and close price of the
previous ordinary candlestick.
x Close price: is the average of open, close, high and low prices of
the previous ordinary candlestick.
x High price: is the highest open or close price from the previous
candlestick.
x Low price: is the lowest open or close price from the previous
candlestick.
Heikin-Ashi charts are slower than candlestick charts as their signals
are delayed. Such delays eliminate a lot of noise and false signals. They
may be used by traders in addition to candlesticks to confirm patterns.
3.3 Types of Markets
Financial markets go through different phases. They can be categorized
into the following:
1. Bull markets;
2. Bear markets;
3. Cycles; and
4. Congested.
A bull market refers to a market on the rise. The price of assets in the
market is increasing. Typical bull markets advance at a gradual pace, and
can last for months or even years. A linear regression of typical bull
markets will have a slope ranging between 150 and 500.
Technical Tools and Technical Analysis
39
Roaring Bull Markets are bull markets with more extreme price
progression. A linear regression of Roaring Bull Markets may have a slope
ranging between 500 and 700. Roaring Bull Markets occur less frequently
than typical bull markets. Furthermore, roaring bull markets tend to be
short-lived.
A bear market is a market with a sustained price decline. Typical bear
markets experience a gradual decline in the prices of assets. The slope of a
linear regression of a typical bear market ranges between -150 and -400.
Panic Bear Markets are the extreme market condition variant of bear
markets. They refer to markets that are experiencing rapid price decline.
They tend to occur as the consequence of mass hysteria or a crash in
financial markets. The Ordinary Least Squares (OLS) regression of panic
bear market tends to have steep slopes ranging between -500 and -700.
The cyclic market, as its name implies, display cycles. It goes from a
short bull to a short bear to another short bull. Or from a short bear to a
short bull to another short bear.
The congested market is characterized by an absence of a trend in asset
price movement. Congested markets tend to display price fluctuations with
no easily recognizable pattern. Congested markets may offer an
opportunity for scalpers trying to make small profits. However, strategies
designed for momentums or reversals may experience a drawdown.
Given that the general market conditions have been identified, the next
section will review chart patterns which in turn reveal the condition of the
market.
3.4 Chart Patterns
Candlesticks can be used to identify various trends in markets. A trend
is a general direction in which the price of an asset is moving. Trends can
vary both in duration and direction. While there are numerous statistical
methodologies that can be used to extract trends from raw data, one of the
more popular tools used by traders are trend lines.
A trend line measures the reaction of investors to the volatility in stock
prices. They are used by traders to determine the best time to enter and
exit certain positions. When traders review raw data on stock prices, they
will see the prices form peaks and troughs. Trend lines can indicate
support levels and resistance levels. The troughs usually represent a low
40
Chapter Three
point in the asset’s price. Traders may enter long positions at these low
points especially when they believe the price will rebound. Likewise, at
peaks traders may believe that the asset’s price may eventually fall,
causing them to lose interest in buying and liquidating their assets. This
activity causes the asset price to decline.
Trend lines can use used to indicate support levels and resistance
levels. The support is the price level in which the stock has difficulty in
falling below. Resistance is the price level in which the stock has difficulty
in rising above. Figure 3.6 provides a display of support and resistance
levels.
Figure 3.06: Resistance and Support
Source: Adapted from Stock Charts (2016a)
Trend lines can be used to construct several patterns. One of the most
basic patterns is the rectangle pattern. In a rectangle pattern, the asset price
fluctuates between support and resistance. In order for a pattern to be
established as a rectangle, both support and resistance must be at least
touched twice. Figure 3.06 also displays a rectangle pattern.
To confirm support and resistance levels, traders may search for
bounces. When a stock price reaches the resistance level, it should
‘bounce’ off resistance and decline. Likewise, when the price reaches
support, it should bounce off support and increase.
Sometimes prices do not bounce off support or resistance. Instead, they
break support or resistance levels. When prices exceed resistance or
support levels, it referred to as a breakthrough or a breakout. An upside
Technical Tools and Technical Analysis
41
break through or upside breakout is where the asset’s price has exceeded
the resistance. This may occur if there is an increase in buying pressure for
the asset. A downside breakthrough or downside breakout is where the
asset’s price falls below support. This occurs when there is an increase in
the selling pressure for the asset. Figure 3.07 illustrates an upside breakout
and a downside breakout.
Where an upside breakout occurs, a previous resistance level may
become a support level. Likewise, where a downside breakout occurs, a
previous support level may become a resistance level. See Figure 3.07.
Figure 3.07: Upside Breakout and Downside Breakout
Source: Adapted from Stock Charts (2016a)
42
Chapter Three
Rectangles can be used to identify an uptrend. An uptrend is a series of
higher peak prices and higher trough prices. In other words, it is an
upward sloping rectangle due to both support and resistance rising over
time. Uptrends and bullish indicators.
Rectangles can also be used to identify downtrends. Downtrends are
the inverse of uptrends. It is a downward sloping rectangle that results
from support and resistance declining over time. Downtrends are bearish
indicators. See Figure 3.09.
Figure 3.08: Uptrend
Source: Adapted from Identifying Trends (2016)
Technical Tools and Technical Analysis
43
Figure 3.09: Downtrend
Source: Adapted from Identifying Trends (2016)
A sideways trend is a sequence of equal peak and low prices. The
rectangle pattern displayed in Figure 3.06 also displays a sideways trend.
Apart from rectangles, trend lines can also form triangles. A triangle is
where there is a convergence in resistance and support levels over time. A
descending triangle is where resistance is declining to converge to support
over time. A rising triangle is where support is rising to converge to
support. A symmetric triangle is where both resistance and support are
converging. Descending triangles are bearish patterns, rising triangles are
bullish patterns, while symmetric triangles are uncertain patterns.
44
Chapter Three
Figure 3.10: Types of Triangles
Source: Adapted from Stock Charts (2016a)
In the evaluation of trends, investors can consider the time horizon for
trends. Trends occurring within 0 to 3 months are referred to as short-term
trends. Trends occurring within 3 to 12 months are referred to as
intermediate trends. Trends lasting periods in excess of 1 year is referred
to as long-term trends.
Rectangles and triangles are continuation patterns. They are called
continuation patterns since the price continues to follow such pattern once
they have been established. However, trends can change over time. In fact,
a stock that was previously experiencing an uptrend can then experience a
Technical Tools and Technical Analysis
45
lower peak price and lower trough price. Alternatively, a stock that was
previously experiencing a downtrend can then experience a higher peak
price and a high trough price. In both cases, then the trend has changed
and resulted in a reversal.
A reversal is a change in the price trend of an asset to the opposite
direction. An uptrend can be reversed to a downtrend. Likewise, a
downtrend can be reversed to an uptrend. See Figure 3.11.
Figure 3.11: Basic Reversal
Source: Adapted from Investopedia (2006)
Chapter Three
46
There are many complex reversal patterns. Some of the main patterns
include:
x
x
x
x
x
Head and Shoulder;
Double Top Reversal;
Double Bottom Reversal;
Falling Wedge; and
Rising Wedge.
The Head and Shoulder is a reversal pattern that is comprised of 1 head
and two shoulders. This pattern is comprised of 3 consecutive peaks
(troughs) in the asset price. However, the middle peak (trough) is higher
(lower) than the other peaks (troughs). The head is the middle peak
(trough) while the shoulders are the 1st and 3rd peaks (troughs). Figure 3.12
provides an illustration of a head and shoulder reversal.
Figure 3.12: Head and Shoulder Reversal
Source: Investopedia (2006)
A Double Top Reversal is a bearish pattern where the asset’s price
made 2 consecutive peaks before making an overall decline. Likewise, a
Double Bottom is a bullish pattern where the asset’s price made 2
consecutive troughs before making an overall increase. See Figure 3.13.
Technical Tools and Technical Analysis
47
Figure 3.13: Double Top and Double Bottom Reversal
Source: Janssen et al. (2006)
Wedges are patterns formed by combining trends with triangles. A
Rising Wedge is a bullish pattern resulting from a combination of a
downtrend and a rising triangle. A Falling Wedge is a bearish pattern
resulting from a combination of an uptrend and a declining triangle. See
Figure 3.14.
Figure 3.14: Rising and Falling Wedges
Source: Adapted from Janssen et al. (2006)
Apart from reversals, another important chart pattern encountered by
traders are flags. A bull flag is a combination of a strong uptrend and a
rectangle. The strong uptrend of often referred as a pole. A Bear Flag is a
combination of a strong downtrend and a rectangle. Some flags form
pennants. A pennant is a combination of a pole and a triangle. A bull
pennant is a combination of a strong uptrend and a triangle, while a Bear
48
Chapter Three
Pennant is a combination of a strong downtrend and a triangle. See Figure
3.15.
Figure 3.15: Flags and Pennants
Source: 4exanalysis (2016)
Another relevant chart pattern that traders encounter is a gap. A gap is
a jump in the price between marketing closing and the next open. Consider
the following example. Assume that the price of an asset closed at $20.
Then the next trading day, the price opened at $50. This space between the
close and the open price is a gap. It is important to note, gaps can be
identified with candlesticks and bar charts, but not line charts as line charts
illustrate continuous movement in the asset’s price. Gaps usually occur
due to a significant event or announcement regarding an asset. The main
types of gas include breakaway, runaway, and exhaustion. Breakaway
Gaps are gaps that mark the occurrence of a new price trend. Runaway
Gaps occur within a price trend. Exhaustion gaps occur at the end of a
price trend.
It is important to note when identifying patterns, it is essential that a
trader tries to confirm these patterns to volume. For instance, if an upside
or downside breakout occurs, there should be an increase in volume as
Technical Tools and Technical Analysis
49
traders may believe a new trend is being established. Reversal patterns are
often accompanied by increases in trade volume as swing traders may try
to capitalize on changing trends.
Figure 3.16: Downside Breakout and an Increase in Trading Volume
Source: Adapted from Stock Charts (2016b)
Charting techniques and pattern recognition can also be used to take
into consideration the psychology of the people in the market. One such
technique is based on the Elliott Wave Theory. The following subsection
discusses the theory in greater detail.
3.4.1 The Elliott Wave Theory
After analyzing 75 years’ worth of stock data, Ralph Nelson Elliott
realized that financial markets are not as chaotic as people thought. In fact,
he found that the market traded in repetitive cycles. He explained that such
cycles were due to the emotions of investors, which in turn was influenced
by news or the predominant psychology of the masses at the time.
Elliott (1938) asserted that the upward and downward swings in the
price of financial assets are caused by the collective psychology of people,
and it always shows up in the same repetitive patterns. He referred to these
upward and downward swings in asset price as ‘waves’. He argued that if
50
Chapter Three
a trader can correctly identify the repeating patterns, they can accurately
predict where the asset prices will go next.
An important aspect of the of the Elliott waves, is that they are fractals.
Fractals are structures which can be deconstructed into part, with each part
being very similar to the whole. In nature, there are many examples of
fractals. For example, a sea-shell, snow-flake, and a cloud are all fractals.
Elliott demonstrated that a trending market can move in a 5-3 wave
pattern. He referred to the first 5-wave pattern as impulse waves, while the
remaining 3-wave pattern is referred as corrective waves. Waves 1, 3, and
5 in the impulse wave pattern are motive, which suggests that they go
along with the overall trend. However, waves 2 and 4 are corrective.
Figure 3.17 provides an illustration.
As seen in Figure 3.17, wave 1 reflects an upward movement in the
price of the currency pair. In this example with real empirical data, there
was relatively strong movement in the price of the EUR-USD currency
pair over the February 2002 to October 2004 period. In wave 2, there is a
contraction in the price of the currency pair, perhaps due to traders finding
the currency pair is overvalued at that point, and closing their long
positions to capture profits. In wave 3, there is another rebound in the
price of the currency pair, its peak is higher than the previous peak in
wave 1 perhaps due to strong speculation by traders in the price of the
currency pair. Eventually, there will be a pullback when traders decide to
close long positions and pull out their profits. Finally, the impulse pattern
ends with an upward sloping wave 5.
The previous example considered a bullish scenario. However, patterns
can also emerge in bear markets. Consider Figure 3.18 which illustrates
both a 5-Wave Impulse Pattern and a 3-Wave Countertrend.
Technical Tools and Technical Analysis
Figure 3.17: 5-Wave Impulse Pattern
Source: FX Choice (2018)
51
Chapter Three
52
Figure 3.18: 5-Wave Impulse Pattern and 3-Wave Countertrends
Source: FX Choice (2018)
In Figure 3.18, the 5-Wave Impulse Pattern can be seen from wave 1 to
wave 5. In contrast to the example in Figure 3.17 which was bullish, this
case is a bearish pattern. After the Impulse Pattern, a 3-Wave Countertrend
emerges as a corrective wave pattern.
As previously indicated, Elliott Waves are fractals. As clearly seen in
Figures 3.17 and 3.18, each wave is comprised of sub-waves. Consider a
more detailed illustration in Figure 3.19.
In Figure 3.19, there is a large Elliott Wave which displays an uptrend
over the October 2017 to April 2018 period for the EUR-USD currency
pair. However, the large Elliott Wave is comprised of a series of smaller
Elliott Waves. The shorter waves occur over a shorter period of time, but
the large waves occur over a longer period of time.
Given that it is possible to distinguish the main waves from the subwaves based on time, the Elliott Wave Theory has proposed a series of
categories for the waves. They are:
x Grand Super-cycle (multi-century);
x Super-cycle (approximately 40–70 years);
x Cycle (one year to several years);
Technical Tools and Technical Analysis
x
x
x
x
x
x
53
Primary (a few months to a few of years);
Intermediate (weeks to months);
Minor (weeks);
Minute (days);
Minuette (hours); and
Sub-Minuette (minutes).
Figure 3.19: Fractals in the Elliott Waves
Source: FX Choice (2018)
The basic principles identified in Elliott Wave Theory can be used to
identify a series of more complex chart patterns. In fact, they can be used
to identify rectangles, triangles, Rising and Falling Wedges, and more
complex patterns.
However, it may be difficult to an uninformed trader to recognize the
correct patterns. When trading based on the basis of the Elliott Wave
Theory, the trader should remember some basic rules to help identify chart
patterns. They are:
1. Wave 3 should not be the shortest impulse wave;
2. Wave 2 should not go beyond the start of Wave 1;
3. Wave 4 should not cross the same price area as Wave 1; and
54
Chapter Three
4. Waves 2 and 4 may frequently bounce off Fibonacci Retracement
Levels.
If the chart pattern does not conform to the aforementioned rules, then
the trader’s Elliott Wave count may be wrong.
Charts should not be analyzed in isolation. Traders often use technical
indicators to verify patterns observed in charts. Technical indicators are
quantitative tools which utilize data on prices of assets to provide
information about their patterns. Technical indicators can be categorized
into leading and lagging indicators. Leading indicators are those indicators
which are designed to precede price movement. Lagging indicators are
those which follow price movements.
The most of the main leading indicators are oscillators.50 Indicators
such as Moving Averages, and Bollinger Bands are lagging indicators. The
aforementioned technical indicators are explored in the next section.
3.5 Oscillators
An oscillator is a Technical Analysis indicator that fluctuates between
set levels or about a central point.51 Oscillators are useful in identifying
patterns, especially when a trend cannot be clearly seen. Oscillators are
used to determine if assets are overbought or over-sold. Some popular
oscillators used by traders include the Momentum Oscillator; the OnBalance-Volume (OBV); the Stochastic Oscillator; the Relative Strength
Index (RSI); and the Money Flow Index (MFI), and Fibonacci
Retracement Levels (FRL).52
50
Oscillators are indicators which are plotted within a bounded range.
Centered oscillators fluctuate around a center point or line. Banded oscillators
fluctuate between upper and lower bands. When the banded oscillator exceeds the
upper band it suggest the asset is overbought. Likewise, the banded falls below the
lower band, it suggests the asset is over-sold.
52
The aforementioned oscillators are the main types encountered by traders and
investors. However, there are multiple modifications to the main oscillators.
51
Technical Tools and Technical Analysis
55
3.5.1 Momentum Oscillator
The Momentum or the Rate of Change (ROC) Oscillator computes
percentage change in the price of an asset.53 It is derived by the following
equation
௣ ି௣೟ష೙
ܴܱ‫ ܥ‬ൌ ೟
௣೟ష೙
‫ͲͲͳ כ‬
(3.01)
where
‫݌‬௧ is the closing price of an asset;
‫݌‬௧ି௡ is the closing price of an asset at period n.
If the rate of change in the asset’s price is increasing, the momentum
oscillator will be increasing. Likewise, if the rate of change is decreasing,
the momentum oscillator will decrease.
3.5.2 On-Balance-Volume
On-Balance-Volume (OBV) is an indicator which that uses the traded
volume of an asset to predict changes in stock price. Granville (1960s)
believed that when the volume of an asset increases suddenly without any
change in price, a change in the asset’s price would soon follow. Likewise,
a sudden decrease in the trading volume would be accompanied by a
decline in the asset’s price.54
3.5.3 Relative Strength Index
The Relative Strength Index (RSI) is an oscillator, introduced by
Wilder (1978), which measures an asset’s price movements.55 The RSI can
be used to determine if an asset is overbought or over-sold. It was
computed via the following equation:
ܴܵ‫ ܫ‬ൌ ͳͲͲ െ
53
ଵ଴଴
ሺଵାோௌሻ
(3.02)
The ROC is a centered oscillator.
The OBV is based on the concept of demand and supply. Increase in demand, as
evidenced by the increase in trading volume would cause the asset’s price to
increase. Likewise, a decrease in demand, as evidenced by a decline in trading
volume would cause the asset’s price to decline.
55
The RSI is a banded oscillator.
54
Chapter Three
56
where
ܴܵ ൌ
ܽ‫ͳݎ݁ݒ݋݊݅ܽ݃݁݃ܽݎ݁ݒ‬Ͷ‫ݏ݀݋݅ݎ݁݌‬
ൗܽ‫ͳݎ݁ݒ݋ݏݏ݋݈݁݃ܽݎ݁ݒ‬Ͷ‫ݏ݀݋݅ݎ݁݌‬
The theoretical range of the RSI is from 0 to 100. If the RSI of an asset
increases to 80 and above, it suggests that the asset is overbought. This
indicates that there may be a pullback56, sending a sell signal to investors.
If the RSI of an asset decreases to 20 or below, it suggests that the asset is
over-sold. This sends a buy signal to investors. It is important to note, the
RSI should be used in conjunction with charts and other tools to accurately
determine what position an investor should take in the market.
3.5.4 Relative Volume
Although by definition it is not an oscillator, the relative volume is a
popular index used in Technical Analysis. The relative volume is a ratio
that compares the current trading volume of a stock to its normal trading
volume for the same time of day. The theoretical range of the relative
volume is 0 to +’. If the relative volume of a stock is 1, it means that the
stock is currently trading at its normal level. If the relative volume is less
than 1, it means that the stock is trading below its normal level. If the
relative volume is above 1, it means the stock is trading more than its
normal level. A relative volume of 2 or higher indicates that a stock is
trading 100% more than it normally trades.57 A relative volume of 2 or
higher can be considered as high.
3.5.5 Money Flow Index
The MFI is a volume-weighted RSI. It is computed via the following
steps.
Step 1: Compute the Typical Price.
ܶܲ ൌ
ሺ௣೓ ା௣೗ ା௣೎ ሻ
ଷ
(3.03)
where
ܶܲ is the typical price;
56
A pullback is a reversal.
A relative volume of 2 indicates that the stock is trading at twice as much it
normally trades.
57
Technical Tools and Technical Analysis
57
‫݌‬௛ is the highest price;
‫݌‬௟ is the lowest price;
‫݌‬௖ is the closing price.
Step 2: Compute the Raw Money Flow
(3.04)
ܴ‫ ܨܯ‬ൌ ܶܲ ‫ܳ כ‬
where
ܴ‫ ܨܯ‬is the raw money flow;
ܳ is the volume traded.
Step 3: Compute the Money Flow Ratio
‫ ܴܨܯ‬ൌ
ሺଵସ௣௘௥௜௢ௗ௣௢௦௜௧௜௩௘ோெிሻ
ሺଵସ௣௘௥௜௢ௗ௡௘௚௔௧௜௩௘ோெிሻ
(3.05)
Step 4: Compute the MFI
‫ ܫܨܯ‬ൌ ͳͲͲ െ
ଵ଴଴
ሺଵାெிோሻ
(3.06)
The MFI is a better measure to identify overbought and over-sold
conditions than the RSI as it takes into consideration both price action and
volume traded.
3.5.6 Stochastic Oscillator
The Stochastic Oscillator compares an assets’ closing price to a
specified its price range over a period of time.58 Like other oscillators, it is
used to determine the best time to long or short an asset. The Stochastic
Oscillator is determined by calculating two values. The first number is
computed via the following equation
Ψ‫ ܭ‬ൌ ͳͲͲሾሺ‫ ܥ‬െ ‫ܮ‬௡ ሻȀሺ‫ܪ‬௡ െ ‫ܮ‬௡ ሻሿ
where
C is the most recent closing price of the asset;
58
The stochastic oscillator is a banded oscillator.
(3.07)
58
Chapter Three
‫ܮ‬௡ is the lowest price of the asset in the period n;
‫ܪ‬௡ is the highest price of the asset in the period n;
By default, n is set to 14 periods.
The second number is calculated via the following equation:
Ψ‫ ܦ‬ൌ ͵‫݂݋݁݃ܽݎ݁ݒܽ݃݊݅ݒ݋݉݀݋݅ݎ݁݌‬Ψ‫ܭ‬
(3.08)
The theoretical range of the Stochastic Oscillator is between 0 and 100.
If the %D or %K is above 80 the asset is considered to be overbought. If
the %D or %K is below 20, the asset is considered to be over-sold. Buy
signals are triggered when both %K and %D are below 20, as it signals a
pending reversal. A sell signal is sent to traders if both %K and %D are
above 80, as it signals a downtrend reversal.
3.5.7 Fibonacci Retracement Levels
Leonardo Fibonacci identified a sequence of numbers that share a
mathematical relationship. The Fibonacci Sequence of numbers is as
follows: 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610 etc. Each
number in the sequence is the sum of the two preceding terms. For
example, 377 = 233 + 144. One of the characteristics of the Fibonacci
Sequence is that each number is approximately 1.618 times greater than
the preceding number. Thus, the Fibonacci sequence can produce the ratio
of 61.8% between a number and its predecessor. In other words, any
number divided by its successor in the Fibonacci Sequence should produce
a ration of approximately 61.8%.
The key Fibonacci Ratios are 23.6%, 38.2%, 50%, 61.8% and 100%.
The 38.2% ratio is derived by dividing a number by its 2nd successor. For
example, 55/144 = 38.19%. The 23.6% ratio is found by dividing one
number by its 3rd successor. For example, 21/89 = 23.59%.
The Fibonacci Ratios can be used to identify critical points in the
movement of financial asset prices on financial markets. In fact, they can
be used to determine points when there may be a reversal in the asset price
(Mitchell 2001). Fibonacci Retracement Levels are the Fibonacci Ratios
(23.6%, 38.2%, 50%, 61.8% and 100%) which are related to the asset
price. Most modern financial trading platforms contain a tool that which
can draw in the lines to identify the Fibonacci Retracement Levels.
Technical Tools and Technical Analysis
59
In order to accurately identify the Fibonacci Retracement Levels
(FRL), a trader should identify the recent significant highs and lows. On
modern trading platforms, the trader can identify the FRLs by clicking the
FRL tool, then click from the most recent highest high to the lowest low to
identify a downtrend, or clicking from the most recent lowest low to the
highest high to identify an uptrend.
Figure 3.20: Fibonacci Retracement Levels
Source: FX Choice (2018)
As can be seen from Figure 3.20, the FRL for XAU/USD were
1242.45 (23.6%), 1244.77 (38.2%), 1246.64 (50.0%), and 1249 (61.8%)
over the June to July 2018 period. The expectation is that if XAU/USD
currency pair retraces from the recent high of 1256.85, it will find support
at one of the FRL as traders may place buy orders at these levels as they
anticipate a price pulls back.
60
Chapter Three
3.5.8 Force Index
The Force Index is an indicator that sends signals about the market
based on the direction and size of the asset’s price movement, as well as
the trading volume. The Force Index may be derived by the following
formula
‫ܫܨ‬ଵ ൌ ሾŽ‘•‡ሺ —””‡–’‡”‹‘†ሻ െ Ž‘•‡ሺ’”‹‘”’‡”‹‘†ሻሿ ‫כ‬
ܿ‫݁݉ݑ݈݋ݒ݃݊݅݀ܽݎݐݐ݊݁ݎݎݑ‬
(3.09)
‫ܫܨ‬ଵଷ ൌ ͳ͵ െ ‫ܫܨ݂݋ܣܯܧ݀݋݅ݎ݁݌‬ଵ
(3.10)
where ‫ܫܨ‬ଵ is the Force Index in period 1; and ‫ܫܨ‬ଵଷ is the 13 point
Exponentially Weighted Moving Average of the Force Index.
The theoretical range of the Force Index is from -’ to +’. Negative
values of the Force Index suggest that the asset price is closing lower than
previous prices. A large negative Force Index indicates that there was a
decline in the asset price, as well as strong trading volume. This also
indicates strong selling power of an asset which is declining in price. Thus,
it may be interpreted as a sell signal. A small negative Force Index shows
that there was a decline in the asset’s price, but weak trading volume.
Thus, it highlights that the downward price movement is a false signal.
A large positive Force Index indicates that the asset price is rising, and
there is strong buying power. Thus, it is a buy signal on a market. A small
positive force index shows the weak buying power associated with the
positive price movement. Therefore, a small positive force index reveals
the positive price movement to be a false signal.
It can be noted that the Force Index is influenced by three (3) majour
variables: the asset price, the magnitude of the price change, and the
amount of trading volume. Large price movements, and large trading
volumes result in large values for the Force Index, and vicey versa.
The Force Index can be used to identify trends and divergences. A
Bullish Divergence occurs where the Force Index is rising from below,
and the asset price was previously decreasing. It suggests that a Bottom
Reversal may occur. Likewise, a Bearish Divergence occurs where the
Force Index is decreasing from above, and the asset price was previously
decreasing. This suggests a Top Reversal.
Technical Tools and Technical Analysis
61
Figure 3.21: The Force Index
Source: FX Choice (2018)
In Figure 3.20, the Bullish Divergence can be seen with the Force
Index moving up from below. Arrow A shows the direction of the Force
Index. The Bearish Divergence can be seen with the Force Index moving
down from above. Arrow B illustrates the direction of the Force Index’s
movement.
It is noteworthy that the Force Index may be used in conjunction with
the RSI to confirm reversals, or in conjunction with Bollinger Bands to
confirm patterns.
Chapter Three
62
3.6 Moving Averages
Patterns can also be established via the use of moving averages. Here,
a Moving Average refers to the average price for an asset over a specified
period. Moving Averages are a simple method to filter out noise59 from the
trend in prices. Moving Averages can have different lengths. For example,
a 10-day Moving Average is the average price of an asset over the past 10day period.
3.6.1 Simple Moving Average
A Simple Moving Average60 is computing by adding up the value of
the asset for a number of periods, then dividing the sum the number of
periods. As the Moving Average moves forward, the oldest value of the
asset is dropped, and the newest value is included. For example
Assume that the closing price of an asset the past 5 days took the
following values:
$21, $23, $27, $22, $21
Then the simple moving average for that period was
̈́ʹͳ ൅ ̈́ʹ͵ ൅ ̈́ʹ͹ ൅ ̈́ʹʹ ൅ ̈́ʹͳ
ൌ ̈́ʹʹǤͺ
ͷ
Assume, on the 6th day, the closing price of the asset was $23. Then if
the Simple Moving Average moves forward it will be:
̈́ʹ͵ ൅ ̈́ʹ͹ ൅ ̈́ʹʹ ൅ ̈́ʹͳ ൅ ̈́ʹ͵
ൌ ̈́ʹ͵Ǥʹ
ͷ
Moving Averages lag asset prices since they are computed from past
prices. In other words, moving averages follow a trend in asset prices. The
longer the time period used to compute the moving average, the greater the
lag in following the asset’s price. Subsequently, moving averages with
longer periods are smoother than moving averages with shorter periods.
59
Noise here refers to random fluctuations in price.
A Simple Moving Average is also referred to as an Equally Weighted Moving
Average.
60
Technical Tools and Technical Analysis
63
For example, consider the following table of prices for an asset over a
period. The information is used to compute a 5-day Moving Average, and
a 10-day Moving Average.
Table 3.01: Prices, 5 day and 10-day Moving Averages
Date
Close
12-Feb-16
16-Feb-16
17-Feb-16
18-Feb-16
19-Feb-16
22-Feb-16
23-Feb-16
24-Feb-16
25-Feb-16
26-Feb-16
29-Feb-16
01-Mar-16
02-Mar-16
03-Mar-16
04-Mar-16
07-Mar-16
08-Mar-16
09-Mar-16
10-Mar-16
11-Mar-16
14-Mar-16
3.6
3.72
3.82
3.5
3.25
3.11
3.25
3.23
2.69
2.69
2.98
3.44
3.47
3.38
3.3
3.2
3.19
3.04
2.9
2.9
2.84
5-day Moving
Average
10-day Moving
Average
3.58
3.48
3.39
3.27
3.11
2.99
2.97
3.01
3.05
3.19
3.31
3.36
3.31
3.22
3.13
3.05
2.97
3.29
3.22
3.20
3.16
3.15
3.15
3.16
3.16
3.14
3.16
3.18
3.17
Source: Yahoo Finance online database (2016)
Observe in Figure 3.21 how the 5-day Moving Average is smoother
than the closing price of Sky Solar Holdings (SKYS) stocks over the
February 12, 2016, to March 14, 2016, period. Also, observe how the 10day Moving Average is smoother than the 5-day Moving Average.
Chapter Three
64
7
6
Price
5
4
3
2
1
0
Axis Title
Close
5 day moving average
10 day moving average
Figure 3.21: SKYS Stocks and Moving Averages
Source: Yahoo Finance online database (2016)
The duration of Moving Averages frequently used in trading include 1minute, 5-minutes, 15-minutes, 30-minutes, 1-hour, 4-hours, 1-day, 5days, 10-days, 50-days, 100-days, and 200-days.
Apart from the Simple Moving Average, there are other moving
averages. Namely:
x the Exponentially Weighted Moving Average (EWMA); and
x the Volume Weighted Moving Average (VWAP).
Technical Tools and Technical Analysis
65
3.6.2 Exponentially Weighted Moving Average
The EWMA computes the average by placing a higher weight on more
recent data, and a lower weight on older data. For example, in the previous
Table 3.01, the simple 5-day moving average placed an equal weight upon
each asset price. In that case, the weight applied to each asset price was
1/5 (20%). If an EWMA is used, it will apply higher weights to the most
recent prices. For instance, the most recent data point can be given a 30%
weight, the 2nd recent a 25% weight, the 3rd recent a 20% weight, the 4th
recent a 15% weight, and the 5th recent a 10% weight. Table 3.02 provides
the data with the EWMA.61
Table 3.02: 5-day EMWA
Date
Close
12-Feb-16
16-Feb-16
17-Feb-16
18-Feb-16
19-Feb-16
22-Feb-16
23-Feb-16
24-Feb-16
25-Feb-16
26-Feb-16
29-Feb-16
01-Mar-16
02-Mar-16
03-Mar-16
04-Mar-16
07-Mar-16
08-Mar-16
09-Mar-16
10-Mar-16
11-Mar-16
14-Mar-16
3.6
3.72
3.82
3.5
3.25
3.11
3.25
3.23
2.69
2.69
2.98
3.44
3.47
3.38
3.3
3.2
3.19
3.04
2.9
2.9
2.84
61
5-day simple moving
average
5-day EWMA
3.58
3.48
3.39
3.27
3.11
2.99
2.97
3.01
3.05
3.19
3.31
3.36
3.31
3.22
3.13
3.05
2.97
3.53
3.39
3.31
3.24
3.06
2.92
2.91
3.04
3.17
3.29
3.34
3.33
3.27
3.18
3.08
3.00
2.93
Note, the EWMA is often used to compute volatility. In such case, variance or
standard deviation is measure of volatility, and the EWMA is used place higher
weights on the more recent data used to compute the standard deviation or variance.
Chapter Three
66
3.6.3 Volume Weighted Moving Average
The VWMA is a price average that takes into consideration the number
of assets traded on a given day. The VWAP is computed via the following
steps:
1. Choose the time period
2. Calculate the typical price for each period.
The typical price (T) is given by ܶܲ ൌ
ሺ‫ ݄݌‬൅‫݈݌‬൅‫ܿ݌‬ሻ
͵
3. Multiply the typical price by the total volume of assets traded in
that period. This will produce TP*Q.62
4. Compute the cumulative TP*Q.
5. Compute the cumulative volume.
6. Divide the cumulative TP*Q by the cumulative volume.
The VWAP is used in conjunction with the MVWAP. The VWAP is
computed daily, but the MVWAP is computed as an average of VWAPs
over a number of days. In other words, the MVWAP is a moving average
of the VWAP.
If an investor purchases an asset at a price lower than the VWAP, then
it suggests that they purchased the asset at a better price than the volume
weighted average price. Likewise, if they purchased the asset at a price
higher than the VWAP, it suggests they paid too much for that asset that
day.
3.6.4 Moving Average Convergence Divergence
The Moving Average Convergence Divergence (MACD) oscillator is a
centered oscillator that is computed from two different period moving
averages. The MACD is derived by subtracting the longer period moving
average from the shorter period moving average. It is given by the
following equation:
62
Recall ܴ‫ ܨܯ‬ൌ ܶܲ ‫ܳ כ‬.
Technical Tools and Technical Analysis
‫ ܦܥܣܯ‬ൌ ͳʹ݀ܽ‫ ܣܯܧݕ‬െ ʹ͸݀ܽ‫ܣܯܧݕ‬
67
(3.11)
Additionally, a 9 day EMA of the MACD is computed and plotted
against the MACD. This 9 day EMA is called the signal line and is used
by traders and investor to determine buy and sell signals. The MACD can
be used to determine crossover trading strategies. Crossovers will be
discussed in greater detail in Chapter 4.
The MACD indicates whether there is convergence or divergence in
the moving averages. Convergence occurs where the two moving averages
are converging towards the same value. Divergence occurs when the two
moving averages are moving apart from each other.
3.7 Bollinger Bands: Another Technical Indicator
A Bollinger Band is a confidence interval that is plotted one standard
deviation above and below a moving average. It can be used to identify
extreme short-term fluctuations in an asset. Standard deviation is used to
create Bollinger bands since it is a commonly used indicator of volatility.
Under normal market conditions, the price of an asset will lie within
the Bollinger bands. The size of the Bollinger Bands will adjust to the
level of volatility in the market. The Bollinger bands experience expansion
when there is an increase in volatility, and contraction when there is a
decrease in volatility.
Bollinger Bands can also be used to identify patterns and changes in
volatility. For instance, periods of low volatility and narrow Bollinger
Bands are often followed by periods of high volatility and wide Bollinger
Bands. Subsequently, a trader observing narrow Bollinger Bands may
anticipate a significant increase in volatility in the near future.
Traders can also inspect the price data to see if they exceed the
Bollinger Bands. If prices exceed the upper Bollinger Band, it suggests
that the asset is overbought, and a reversal may occur in the near future.
Conversely, if the prices exceed the lower Bollinger band, it suggests that
the asset is over-sold, and rapid rise in prices may occur in the near future.
Figure 3.22 provides an illustration of Bollinger Bands. The Bollinger
Bands are around the candlesticks. Observe how the Bollinger Bands
contract and become narrow during periods of low volatility, but expand
and become wide during periods of high volatility. In can also be noted
Chapter Three
68
from the example in Figure 3.22 that most of the price movement occurred
within the Bollinger Bands.
Figure 3.22: Bollinger Bands
Source: FX Choice (2018)
Technical indicators are tools used by traders and investors to create
trading strategies. Chapter 4 will consider various trading strategies in
greater detail.
3.8 Linear Regression Models
Technical Analysis involves the analysis of price data to provide sight
about the direction of the market, which in turn can be used inform the
decisions of retail traders in their trading activities. Linear regression
models can be very useful for trading as they can be used for the
forecasting.
Regression is a statistic tool that is used to evaluate the relationship
between a given variable and one or more other variables. A linear
regression is a statistical technique which takes a linear approach to
modeling the relationship between a scalar response (or dependent
variable) and one or more explanatory variables (Brooks 2008; Freedman
2009). More simply expressed, a linear regression is a statistical technique
Technical Tools and Technical Analysis
69
which tries to determine a relationship between one variable and other
variables by plotting a straight line exactly through the middle-dispersion
of the data points of all the variables.
There are many different regression models. The first linear regression
which is introduced to students of econometrics is the Classical Linear
Regression Model (CLRM). The CLRM, also referred to as the Ordinary
Least Squares (OLS) model is determined by regressing a variable upon
other variables. During the process, a straight line is used to fit or match
the general pattern of the data. However, there is highly unlikely there will
be a perfect fit or match between the actual data and the line, especially if
financial data is used. Thus, there will be positive errors, where the line is
above the actual data, as well as negative errors, where the line is below
the actual data. What the OLS method seeks to do is plot a line through the
middle-dispersion of the data of the variables while minimizing the sum of
the squared errors. Consider Figure 3.23.
Figure 3.23: Scatterplot of Two Variables
Source: Brooks (2008)
Figure 3.23 Part A displays a scatterplot of two variables x and y. In
Figure 3.23 Part B, the OLS method is used to plot a line exactly through
the middle-dispersion of the data. It minimizes the sum of the positive
errors as well as the negative errors. In fact, it is highly desirable for the
Chapter Three
70
OLS model to be applied in such a way that the positive errors cancel out
the negative errors, resulting in the value of zero for the average or
expected error term.
Economist and econometricians take regression analysis even further.
Each line can be equation. A straight line can be expressed in the form of
ܻ ൌ ‫ ܣ‬൅ ‫(ܺܤ‬3.12)
where A is the point where the line intercepts the Y axis, B is the slope
or gradient of the line, and Y and X are two variables.
This same concept can be applied to the OLS model. In fact, in
equation (3.12), Y is the dependent variable whose value is influenced by
the values of variable X. Parameters A and B are estimated via the OLS
method. The parameter B is the import parameter of interest in linear
regressions since it is the coefficient that indicates the marginal effect. In
other words, in an OLS model, the B coefficient indicates the magnitude to
which the variable Y will change when there is a change in variable X.
Econometrics students are required to note that OLS models are based
on the following assumptions:
1. the model is linear, ܻ ൌ ‫ ܣ‬൅ ‫;ܺܤ‬
2. the expected value of the errors is zero, ‫ܧ‬ሺ‫ݑ‬௧ ሻ ൌ Ͳ;
3. the variance of the errors is constant, ‫ݎܽݒ‬ሺ‫ݑ‬௧ ሻ ൌ ߪ ଶ ;
4. the errors are linearly independent of one another, ܿ‫ݒ݋‬ሺ‫ݑ‬௧ ǡ ‫ݑ‬௧ିଵ ሻ ൌ
Ͳ; and
5. the estimated parameters are unbiased, ‫ܧ‬൫ߚመ൯ ൌ ߚ.
Properties 3-5 are the properties for white noise. In summary, white
noise is a standard used to verify that a linear regression model is robust. It
requires that i) the estimated parameters must be unbiased, and be true
representations of the actual parameters; ii) there must be a presence of
homoscedasticity and an absence of heteroscedasticity, as evidenced by
the constant variance of the error term; and iii) the absence of serial
correlation, so that errors of the past must not affect errors of the future.
Apart from the OLS model, another popular model that is introduced to
students of financial econometrics is the Autoregressive Integrated
Moving Average (ARIMA) model. The ARIMA model is a univariate
Technical Tools and Technical Analysis
71
model. In other words, it is a regression that can model the outcome of a
variable as a function of past values of itself, and past errors in estimation.
Mathematically, this may be expressed as
ܻ௧ ൌ ߙ ൅ ߚଵ ܻ௧ିଵ ൅ ‫ ڮ‬൅ ߚ௣ ܻ௧ି௣ ൅ ߠଵ ‫ݑ‬௧ିଵ ൅ ‫ ڮ‬൅ ߠ௤ ‫ݑ‬௧ି௤ ൅ ߝ௧ (3.13)
where the variable Y in period t, is the dependent variable, variables
ܻ௧ିଵ and ܻ௧ି௡ denote time lags in variable Y to previous periods, ‫ݑ‬௧ିଵ and
‫ݑ‬௧ି௤ denote lags in the error term, ߙǡ ߚǡand ߠ are estimated parameters,
and ߝ௧ is the current error term.
The ARIMA (p,d,q) model is attractive, especially in the case of
financial data, because it allows a researcher to model stocks, forex, and
other asset prices as a function of their own past values, without taking
into consideration the values of other variables. The ‘p’ refers to the order
of the autoregressive component in the ARIMA model. In other words, it
indicates how many lags of the dependent variable will be included in the
model. The ‘q’ refers to the order of the moving average component.
Alternatively expressed, it indicates how many lags of the error term is
included in the model.
The ARIMA model incorporates the concept of stationarity. In
simplistic terms, stationarity refers to the extent to which the statistical
properties of a time series is constant over time. There is strong sense and
weak sense versions of stationarity. In the strong sense, stationarity
requires all the moment conditions of a time series to be independent of
time. Whereas weak sense stationarity is where the mean and variance of a
time series is independent of time.
Stationarity is a very important concept in financial econometrics. If a
time series mean and variance changes with every observation, then a
linear regression model will not be able to make accurate predictions about
future values of the dependent variable. For this reason, it is highly
desirable for a time series to be stationary, at least in the weak sense.
In the ARIMA (p,d,q) model, the ‘d’ refers to the order of integration
or the extent to which a time series used in the regression is stationary.
Usually, before applying the ARIMA (p,d,q) model, the researcher/
analyst63 would be required to perform a series of tests for stationarity.
63
Note, here the person performing the test is referred to as a researcher or analyst
as it typically requires some training in econometrics to undertake such
Chapter Three
72
Tests such as the Augmented Dicky Fuller (ADF), the Phillips Peron (PP),
and the Kwaitkowski-Phillips-Schmidt-Shin (KPSS) tests can be
performed for stationarity. A more technical researcher could consider
tests such as the Perron (1997), the Zivot and Andrews (1992) tests for
stationarity in the presence of structural breaks. However, such tests are
not explained in detail as they are beyond the scope of this book.
If a series is found to be stationary, also denoted as I(0), then the
researcher may use the raw data in the ARIMA model. If the data is found
to be non-stationary, and containing 1 unit root, also denoted as I(1),64
then the researcher would be required to apply a first difference65 to the
time series to make it stationary before specifying the ARIMA (p,d,q)
model.
The correct order of the ‘p’ and ‘q’ are determined by applying the
Box-Jenkins Iterative Process. Box and Jenkins (1976) were the first to use
a systematic approach to specify ARIMA (p,d,q) models. Their approach
involved three steps:
Step 1: Identification;
Step 2: Estimation; and
Step 3: Diagnostic Testing.
In the Identification Step, the graphs of the Autocorrelation Function
(ACF) and Partial Autocorrelation Functions (PACF) are used to suggest
the order of ‘p’ and ‘q’. For an Autoregressive (AR) process the ACF does
not vanish but the PACF number of significant spikes will determine the
AR (p) process. For a MA (q) process, the PACF does not vanish, and the
number of significant spikes for the ACF will suggest the order of the MA
(q) process. Consider the example in Table 3.04.
assignment. In other words, it is typically a more advanced trader with an
understanding of financial econometrics that would perform such task.
64
It is possible for a non-stationary series to contain 2 unit roots. However, the
basic stationary tests (ADF, PP, and KPSS) usually indicate that a time series
contain 1 unit root.
65
A first difference is a basic transformation that involves the subtracting 1 lag of
a variable from itself. It may be denoted by ݀ሺ‫ݕ‬௧ ሻ ൌ ‫ݕ‬௧ െ ‫ݕ‬௧ିଵ . Such
transformation allows and I(1) series to become weak sense stationary, I(0).
Technical Tools and Technical Analysis
73
Table 3.04: ACF and PACF
Included observations: 261
Autocorrelation
Partial Correlation
.|**** |
.|**** |
.|*** |
.|*** |
.|** |
.|*** |
.|** |
.|** |
.|** |
.|* |
.|**** |
.|** |
.|. |
.|* |
.|. |
.|* |
.|. |
.|. |
.|. |
*|. |
AC
PAC Q-Stat Prob
1 0.530 0.530 74.065 0.000
2 0.479 0.276 134.86 0.000
3 0.347 0.025 166.83 0.000
4 0.345 0.111 198.58 0.000
5 0.268 0.009 217.78 0.000
6 0.336 0.160 248.15 0.000
7 0.302 0.062 272.82 0.000
8 0.258 -0.033 290.87 0.000
9 0.226 0.009 304.73 0.000
10 0.159 -0.069 311.65 0.000
In Table 3.04, the ACF does not vanish, indicating an AR process.
Since it appears to have 2 significant spikes in the PACF it suggests that
the process could be an AR (2). With regards to the MA, the PACF seems
to vanish after 2 significant spikes. This may suggest that there is no MA
process. Thus, the output in Table 3.04 seems to suggest an ARMA (2,0)
model.
In the Estimation Stage, the researcher would have to estimate the
parameters of the model using econometric software. Some popular
econometrics software used by researchers include Eviews, Stata, SPSS,
R, and MatLab. Eviews, Stata, SPSS are generally Graphical User
Interface (GUI) type software. Thus, a researcher has a menu of options
which they can graphically navigate through in order to specify a model. R
and MatLab are programming type software, which relies primarily on
codes to perform all operations. Modeling performed in R and MatLab are
undertaken by researchers with a good understanding of the programming
language as well as econometrics and mathematics. This book does not go
into detail about explaining how to use econometric software.
In the Diagnostic Testing Stage, the researcher is required to perform a
series of tests to verify model authenticity. The first diagnostic test a
researcher must specify is a test for white noise. Recall, white noise is the
absence of serial correlation, the absence of heteroscedasticity in the error
term, and the unbiasedness of the estimated parameters. Although 3
principles are used to establish white noise, in practice, white noise is
investigated by testing for serial correlation. The Ljung-Box test is
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Chapter Three
frequently used to test for serial correlation in ARIMA (p,d,q) models.
Models that fail the white noise test must be abandoned and re-estimated.
Models that pass the white noise test may proceed to further tests to verify
robustness.
Additional tests which should be applied include heteroscedasticity
tests, normality tests, tests for the statistical significance of each
parameter, and tests for the joint statistical significance of all the estimated
parameters.
While the aforementioned econometric analysis may sound very
complex for a new trader, it can be very easily applied by the new trader.
In fact, traders with absolutely no knowledge about econometrics can
apply a linear regression model to real life financial data while on a
broker’s platform. This is attributed to many brokers offering a tool to
undertake linear regression on their platform. Consider Figure 3.24.
Figure 3.24 displays the information for the USD/JPY currency pair
over the October 2017 to June 2018 period. A linear regression model was
applied to the USD/JPY currency pair data for the 2 January 2018 to the 2
April 2018 period. While a ߚ coefficient was not produced by the model, it
managed to display a downward sloping pattern for the USD/JPY currency
pair over the corresponding time period. Thus, anyone can easily identify
that the USD/JPY currency pair was displaying a bearish pattern during
that period.
While such linear regression model offered by a broker is very easy to
use, it contains a significant limitation. Observe over the 2 October 2017
to the 2 January 2018 period that the USD/JPY currency pair was moving
in a horizontal direction, over the 2 January 2018 to the 2 April 2018
period the USD/JPY currency pair was moving in a downward direction,
but over the 2 April 2018 to the 29 June 2018 period the USD/JPY
currency pair became bullish. Any linear forecast based solely on the data
from the 2 January 2018 to the 2 April 2018 period would forecast bearish
and declining prices for the USD/JPY currency pair. The linear regression
models would not be able to identify that a turning point would occur
around 2 April 2018, and the market would reverse to bullish conditions.
Thus, linear regression models can be misleading.
Technical Tools and Technical Analysis
75
Figure 3.24: Linear Regression Model
Source: FX Choice (2018)
A number of approaches have been developed to address such
limitation of linear regression models. One approach is to apply the
concept of structural breaks66 and specify a regime switching model67. The
model would have piecewise linearity68, but as a whole, it would be
considered as non-linear. An alternative approach is to use a more
complex non-linear model, such as an Artificial Neural Network (ANN)
model, or a Machine Learning model. ANNs and Machine Learning
models are increasingly used to help inform the trade of stocks, forex, and
other financial assets. However, ANNs and Machine Learning models are
relatively complex, and are executed by advanced traders. Both ANNs and
Machine Learning models are outside the scope of this book.
66
A structural break is a specific point in a line where there could be a change in
its gradient, its y-axis intercept, or both. In financial markets, structural breaks tend
to occur very frequently. They are often a response of asset prices to significant
events.
67
A regime switching model is used to model non-linearity in data by assuming
different behavior (structural break) in one subsample (or regime) to another.
68
Piecewise linearity is where parts of a regression model are linear. In other
words, the regression model is made up of different parts, but each part is linear.
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Chapter Three
3.9 Summary Insight
Technical Analysis is a very important and useful analytical framework
that is used by retail traders to help inform their decisions. Unlike
Fundamental Analysis which places greater emphasis on the evaluation of
an asset’s intrinsic value, Technical Analysis focuses on the price
movements in charts, and various indices to evaluate an asset’s
performance, and the potential direction in which the price of the asset
may go.
This chapter examined the basics principles of Technical Analysis that
a retail trader should know before entering the market. A retail trader
should be fully aware of what are candlesticks, how to interpret them, how
to analyze candlestick charts, and how to recognize chart patterns.
Furthermore, the retail trader should know what indices, and oscillators
would be able to adequately complement their analysis of charts.
A wide range of Technical Analysis tools are available. Heikin-Ashi
charts react slower than regular candlesticks, thus they are good indicators
of medium-term to long-term patterns as their delayed signals eliminate a
lot of noise. Moving Averages are a popular tool used by retail traders to
identify trends, crossovers, and long-term changes in the market direction.
Regular candlestick charts, Heikin-Ashi charts, and Moving Averages
can be complemented by indices such as the RSI, the ROC Oscillator, and
the OBV. Likewise, Fibonacci Retracement Levels can be used to identify
potential resistance and support levels, which in turn could highlight
possible turning points.
Retail traders can also use linear regressions to plot the general
direction of the market. More advanced traders can input asset price data
in econometric software to run specific econometric models and determine
the direction of the market. In fact, the most advanced traders would be
able to use advanced models such as ANNs and Machine Learning models
to forecast future prices of assets.
The Technical Analysis tools explored in this chapter can all be used to
inform a trading strategy of a retail trader. Trading strategies are discussed
in greater detail in Chapter Four.
CHAPTER FOUR
TRADING STRATEGIES
4.0 Introduction
Trading is more than just randomly selecting stocks to long or short.
Successful economic agents typically rely upon a trading strategy to profit
from trading. In fact, it is difficult for any trader to consistently generate
gains on a long run basis without a systematic approach.
There are multiple types of trading strategies.69 Some trading strategies
are simplistic and can be implemented by the average trader. Other
strategies are more sophisticated and rely on computerized software and
machines.
This chapter considers some simple trading strategies which can be
implemented by the average economic agent.
4.1 Trading Strategies
A trading strategy is a set of rules a trader uses to decide when to enter
and close a trade. Trading strategies utilize both trade filters and triggers.
A trade filter is the set of conditions that must be met in order for an asset
to enter the watch-list for a trade. A trade trigger identifies the exact point
where a trade will be entered.
All trading strategies should have rules for entry, rules for exit, rules
for risk management, and rules for position sizing. Entries are the points
the trader has identified to enter trades. They can be filtered by a number
of conditions. For instance, the trader can specify an entry position at the
69
It is important to note, investing also has strategies. For instance, an investor
may adopt a value investing strategy in which they first attempt to identify stocks
whose price is undervalued relative to their long run fundamentals, and then take a
long position on the stock. They may select stocks with lower than average priceto-book ratios, lower than average price-to-earnings ratios, or higher than average
dividend yields.
78
Chapter Four
open price at the market open, or the close price for a market close. Or,
after confirming a chart pattern, the trader can set an entry position as the
first or second candlestick that is consistent with the identified pattern.
Exits can specify positions that would minimize a loss, or close a
winning position after a target profit has been achieved.
All trading strategies will carry some risk, as there will always be a
possibility that the market participant can incur some loss. The most
successful trading strategies are those which minimize loss whenever they
occur. This does not mean the total elimination risk. Rather, it cuts the
losses early and allows the trader to move on.70
Position sizing refers to the number of shares or contracts a market
participant risks with each trade. It is dependent upon size the trading
capital of the market participant. Obviously, traders with larger trading
capital would be able to take larger positions than traders with small
trading capital.71
Apart from the main rules, trading strategies can also be arranged in
different categories. Some main types include crossovers, momentum,
volatility breakouts, reversals, event trading, and Heikin-Ashi.
4.1.1 Crossovers
A crossover is a basic trading strategy that is based on the price or
moving average of an asset moves from one side of a longer moving
average to the other side. Crossover trading strategies can be generalized
into two types: a price crossover, and a moving average crossover.
A Price Crossover occurs when the price of an asset increases above
(or decreases below) a moving average of that asset. For example, assume
that the price of an asset was initially below its 5-day moving average. If
the price of the asset suddenly increases and exceeds the 5-day moving
average, then a price crossover strategy has occurred.
A Moving Average Crossover occurs when a moving average of an
asset crosses over another moving average of a longer length. For
example, assume that the 5-day moving average of an asset was initially
below the 10-day moving average of the asset. Then, assume the price of
70
71
Risk management is discussed in greater detail in Chapter Five.
There are advanced position sizing techniques such as adjusting to volatility,
Trading Strategies
79
the asset significantly increases causing the 5-day moving average to
increase. If the 5-day moving average exceeds the 10-day moving average,
then a moving average crossover has occurred.
Price US $
Crossovers are used by traders to identify changes in trends. They can
be used to determine if an asset’s price is breaking resistance or support,
signaling a new uptrend or downtrend. Price Crossovers will occur more
frequently than moving average crossover. However, they may send false
signals to traders. Traders searching for breakouts on the basis of Price
Crossover strategies may identify inaccurate trends as support or
resistance may not be broken. Indeed, assets whose prices are highly
volatile may crossover short moving averages on a frequent basis, but this
does not necessarily mean a new uptrend or downtrend has occurred.
4
3.5
3
2.5
2
1.5
1
0.5
0
Trovw Close
5-day MA
10-day MA
Figure 4.01: Price Crossover of TROVW Stocks, Jan 4 – Jan 26, 2016
Source: Yahoo Finance (2016)
As can be seen by Figure 4.01, the Trova Gene, Inc (TROVW)
appeared to experience a Price Crossover on Thursday, January 21, 2016,
as its stock price (US $3.5 exceeded its 5-day moving average (US$1.87).
The closing price of Trova Gene’s stock also crosses the 10-day moving
average on the same day. Traders and investors may want to confirm a
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80
new trend and may wait for a moving average crossover before they
decide to ride a momentum. Since a moving average crossover does not
occur in the displayed period, the price crossover may be a false indication
of an uptrend.
Price US $
Consider Figure 4.02 which illustrates the price of Trova stocks over a
longer time period. A Moving Average Crossover occurs initially on
Wednesday, January 27, 2016, as the 5-day moving average exceeds the
10-day moving average. However, this does not last long as the 5-day
moving average falls below the 10-day moving average a few days later.
Another Moving Average Crossover occurs on Thursday, February 11,
2016. The data clearly shows this Moving Average Crossover last 6 days.
Thus, the second moving average crossover may be a better indicator of a
new trend than the Price Crossover.
4
3.5
3
2.5
2
1.5
1
0.5
0
Trovw Close
5-day MA
10-day MA
Figure 4.02: Price Crossover of TROVW Stocks, Jan 4 - Feb 22, 2016
Source: Yahoo Finance (2016)
Note, in Figure 4.02, the Price Crossover always occurred before the
Moving Average Crossover. Thus, a Moving Average Crossover would be
a better indication of a new trend than the price crossover as a moving
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81
average crossover would only occur after an uptrend or downtrend has
been established.
Crossovers may be bullish or bearish. A Bullish Crossover occurs
when the price (or short Moving Average) increases above the Moving
Average (or longer Moving Average). It signals an uptrend. Traders or
investors may take a long position. A golden cross is a bullish crossover. It
occurs when the 50-day Moving Average moves above the long-term,
200-day average.
A Bearish Crossover occurs when the price (or short moving average)
decreases below the Moving Average (or longer Moving Average).
Bearish Crossover sends signals of downtrends. Traders or investors may
subsequently take short positions or exit previously long positions. A
death cross is a bearish crossover. It occurs when the short-term, 50-day
moving average, decreased below the long-term, 200-day moving average.
Many traders and investors may use multiple moving averages to
establish changes in trends. For example, an investor may use a 50-day
moving average crossing a 100-day moving average in addition to a 50day moving average crossing a 200-day moving average. Note, the latter
Moving Average Crossover Strategy would be an indicator of a trend since
a trend must be established before the moving average crossover occurs.
Furthermore, longer Moving Average Crossovers are better indicators of
long-term trends while shorter Moving Average Crossovers are better
indicators of the short-term trend.
An investor would be interested in utilizing long length moving
average crossover strategies as they are interested in the long-term
direction of the market. They would prefer a moving average crossover
strategy that is slow to react to short-term price fluctuations in the market.
Thus, a 50-day Moving Average crossing a 200-day Moving Average, and
a 100-day Moving Average Crossing a 200-day moving average would be
of interest to an investor.
A day trader would be interested in short horizon moving averages. For
instance, a day trader may utilize a 5-minute moving average crossing over
a 10-minute moving average and a 10-Minute Moving Average Crossing
over a 15-Minute Moving Average. This sends short-term signals to
traders when to enter or exit positions.
There is no perfect moving average length. The type of moving
average selected and used by a trader or investor would depend upon their
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Chapter Four
trading strategy, their aversion to risk, and the duration of time in which
they intend to hold their asset.
In addition to crossovers, traders and investors may utilize filters to
confirm patterns and determine when to trade. For example, an investor
trading on a 10-day Moving Average crossing over a 50-day Moving
Average may wait until the 10-day moving average is at least 10% above
the 50-day Moving Average before entering a trade. The filter is used to
validate the crossover and decrease false signals. The downside to relying
on filters is that trends are identified after they occur, thus the investor
may lose out on some of their potential gains.
Although in the previous examples in this section, the Simple Moving
Average Crossover was used, a trader can opt to use Exponentially
Weighted Moving Averages for their crossover strategy. The type of
Moving Average used will depend upon the trader’s tolerance for false
signals.
4.1.2 Moving Average Envelopes and Bollinger Bands
Moving Average Envelopes are another type of trading strategy that
utilizes moving averages. It involves constructing a confidence interval
(perhaps a 10% confidence interval) about a medium-term moving average
(perhaps a 25-day moving average) to identify support and resistance
levels. If the price of the asset moves beyond this 5% confidence level, it
sends signals to the investor/ trader. For example, assume the price of an
asset moved below 10% of the 25-day moving average. This suggests to
the investor that the price of the asset has broken support and may be
experiencing a downtrend.
Alternatively, a Bollinger Band can be used instead of the moving
average envelope. If the price of the asset moves above 1 standard
deviation from the moving average, it suggests to the investor that the
asset’s price has broken resistance and an uptrend is occurring.
Subsequently, the investor/ trader may take a long position on the asset.
4.1.3 Momentum
Momentum trading is where traders trade stocks that are moving
significantly in one direction on high volume. The trader uses technical
analysis to determine the overall direction of the market, and then enters a
position which would allow them to earn a profit. It the trader identifies a
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83
bullish trend, they will take a long position to ride the momentum.
Likewise, it the trader establishes a bearish trend, they will short sell the
stock with the intention to cover at a later point and earn a profit.
To satisfy the trading condition, the stock price should break resistance
or support. Secondly, the stock should be trading at relatively high
volume. The upside breakout can be identified by the stock price trading at
a new high. Likewise, the downside breakout can be identified by the
stock price trading at a new low. More sophisticated traders may use
econometric techniques, or computerized software to established support
and resistance levels, and breakouts. However, those advanced methodologies
are outside the scope of this book. This book is geared towards the novice
trader than is aspiring to increase their knowledge base.
Alternatively, a trader can establish their own rules to facilitate
momentum trading. For instance, as a condition to long a stock, a trader
may require the most recent candlestick to breakout and set a new high
over the last ‘N’ candlesticks. If ‘N’ is set at 5, then, once the last
candlestick has broken the high of the previous 5 candlesticks, it would
send a buy signal to the trader.
Another example of rules to establish a buy signal, a trader may require
the second candlestick to step outside of the Bollinger Bands. Since the
majority of the stock price movement occurs within the Bollinger Bands,
movement outside the bands can be interpreted as a breakout.
A third example of trading rules, a trader could require that the last
candlestick rise by at least ‘X’ percent of the previous ‘N’ candlesticks,
and the high of the last candlestick to be greater than the high of the
previous 2N bars. For example, the trader can enter the long position if the
last candlestick to rise by more than 0.5% over the previous 3 candlesticks,
and the high of the last closed candlestick to be greater than the highs
achieved over the previous 6 bars. The trader can experiment with
different values for ‘X’ and ‘N’, and choose the options that generate the
most profitable trades.
The aforementioned trading rules can also be supported by increases in
trading volume. For instance, the trader may also require the trading
volume to increase by at least ‘X’ percent, in addition to the stock price
changes. Or the trader can require a relative volume of at least 2 in order to
confirm the new momentum. Such a strategy is sensible since the trading
volume should increase when new trends emerge.
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Day traders also search for parabolic moves. A parabolic move is an
exponential change (increase or decrease) in the stock’s price. Parabolic
moves can occur as a consequence of a stock responding to news. Good
news regarding a company’s sales and its profitability should cause
upward price movement. Bad news regarding a company’s profitability or
public relations tends to cause a negative stock price movement.
4.1.4 Volatility Breakouts
A Volatility Breakout is a trading strategy based on trading upside and
downside breakouts. It based on the premise that if the market moves a
certain percentage in excess of resistance or support a breakout will occur.
To capitalize on a breakout, a trader’s strategy should have conditions
that must be made before marking an entry. For instance, the trader may
require at least three (3) 5-minute candles to break resistance, as well as
the relative volume to be greater than 2, in order to go long. The strategy
may also include a rule for the position size (perhaps 5% of the total
equity), and a rule for exit (perhaps closing the order after on the first 1minute candle to make a pullback after achieving at least a 15% gain).
Like most trading strategies, Volatility Breakouts have the potential for
profits or losses. If a trader interprets false signals they may incur losses.
For example, if a trader wrong mistake a 1-minute candle rising above
resistance by 10% for a breakout, they may go long. However, a reversal
may occur instead with the asset’s price. Thus, by going long, the trade
took the wrong position and may incur a large loss.
Due to the occurrence of false signals, traders may use delayed
indicators to identify breakouts in order to avoid false signals. For
instance, the trader may require an Exponentially Weighted Moving
Average to also break resistance or support to confirm the pattern. The
downside of using delayed signals is that by the time they confirm a
pattern, the pattern may soon end, and the trader may have lost the
opportunity to earn a profit.
4.1.5 Reversals
A Reversal Trading Strategy is based upon trading reversals. The
trader performs Technical Analysis to identify reversals, and then make
the appropriate trade.
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85
The RSI is a useful indicator to identify reversals. As previously
mentioned, if the RSI is greater than 80, it suggests that a stock is
overbought. This indicates a possible reversal for the trader. Thus, the
trader using the reversal strategy may short sell the asset. Likewise, an RSI
less than 20 suggests that a stock is oversold. A trader using the reversal
strategy would go long on the asset.
Cautious traders may set their own more stringent conditions when
trading on a reversal. For instance, they may require the RSI to drop below
10 to go long, or the RSI to rise above 90 to go short. This can be
supplemented by the trader looking for at least 1 candlestick to reverse,
after about 3 consecutive 5-minute candlesticks of the same color has hit
resistance or support. Ideally, the trader should try to catch the stock as
close to resistance or support as possible in order to earn larger profit
margins when trading reversals.
4.1.6 Events Trading
In the case of stocks, news on a company’s financial health,
profitability, operational challenges, as well as scandals can all affect the
price of stocks. Macroeconomic news which can affect the financial health
of the company can also affect stock prices.
In the case of forex markets, currency pairs tend to react to major
economic news. While the major currency pairs react to most economic
news from developed and influential countries, the biggest movers and
most watched news come from the US (Bauwens et al. 2005; Roache et al.
2010; Lahaye et al. 2011). The reason is that the US has the largest
economy in the world and the US Dollar is the world’s reserve currency
(Reinbold and Wen 2018). This means that the US Dollar is a participant
in the majority of all forex transactions (Blinder 1996; Forest et al. 2018).
Economic news on the US economy such as GDP growth, inflation
rate, and the Federal Reserve’s (Central Bank) repo rate all can influence
the market speculation and the extent to which the US moves against other
countries. Geopolitical news on events such as war, natural disasters,
political unrest, and elections can also affect speculation on the US dollar.
For example, in May 2007, the seasonally adjusted unemployment rate
in the US was 4.4%. However, as the financial crisis and economic
recession took root in the US, the unemployment rate quickly rose to 10%
by October 2009 (US BLS 2018). Such rising unemployment reflected a
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Chapter Four
weakening of the US dollar. Thus, there was no surprise when the US
dollar depreciated against major currencies during the associated period
(Fratzscher 2009).
A retail trader basing their trading mainly on news can do so by
looking for a period of consolidation ahead of the release of routine
economic news, then trading on the breakout. Positions taken in news
based trading can be held for a short moment (as in intraday trading) or for
a few days depending on the news.
In short, good news cause financial assets (stock prices and currency
pairs prices) to increase, while bad news causes the financial assets prices
to decline. In the case of stocks, this arises due to multiple traders going
long on a stock after reports of good news, increasing demand and rising
price. Whereas bad news is accompanied by traders closing long positions,
or short selling, causing a decline in demand, and the decline in the stock
price.
The practice of trading based upon news is known as event trading.
Consider an example, on Tuesday 25 April, 2017, Nord Anglia Education
Inc., a Hong Kong-based operator of international schools, announced that
it would be bought by the Canada Pension Plan Investment Board and
Baring Private Equity Asia for US$4.3 billion. The positive news of the
acquisition caused the price Nord Anglia Education Inc. (NORD) stocks to
increase by 17.38% by 10:00 am on the same day.
If a trader takes a correct position based on news and catches the
momentum early, windfall profits are the result. Conversely, if the trader
took the wrong position, or continued to hold the wrong position in the
aftermath of bad news, large drawdowns can occur. Likewise, traders that
trade based on black swan events72 can earn huge profits or losses
depending on whether they took the correct position or not.
Consider a hypothetical example. Assume that a publicly traded stateowned oil company was poorly managed and it was one the verge of
bankruptcy. Assume this information was announced on the news. The
obvious reaction of people hearing such news would be to sell off their
72
Black swan events are extremely rare events that can have huge effects on
financial markets. They are random and highly unpredictable. Some examples
include the Wall Street Crash of 1929 and its associated Great Depression, the dotcom bubble of 2001, the 2008 US housing market crisis and associated financial
crisis.
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87
stocks of that state-owned oil company. Assume that a person who had
stocks of the state-owned oil company heard about the company’s problem
the day before it was announced on the news. In such a case they would
sell out all of their stocks and would be able to make more profit than if
they had waited on the news. Hence trading based on news would be more
beneficial to the retail trader than trading without consideration of news.
Note, when stakeholders of a company trade based on information
before it is released in the news it is called insider trading. Such activity is
considered unethical and is illegal in many countries.
Significant news tends to increase the volume of trade of the affected
stocks, currency pairs, or financial assets. In the forex market, since the
volatility tends to increase when significant news are released, many forex
brokers tend to widen the spread between bid and ask. For example, the
spread between a currency pair may be comprised of a bid price of
US$1.258 but an ask price of US$1.260. The difference between
US$1.258 and US$1.260 is 0.0002 or 2 pips.
When trading with market orders during periods of news related
volatility, market orders can be filled at a significantly different price to
what the retail trader intended. For example, the ask price of a currency
pair may be US$1.260. The trader may go long and purchase the currency
pair because they believe that the bid price may rise to a value
significantly higher than US$1.260. However, assume the trader place a
long market order during a moment of extremely high volatility. It is
possible for the order to be filled at an ask price significantly higher than
US$1.260. If that occurs, it would now take more upward price movement
to cover the bid-ask spread, as well as the cost of commission in order for
the trader to generate a profit.
The same problem can occur on the downside, causing the retail trader
to experience slippage. Consider another example. Assume the trader
anticipating a decline in the market placed a short market order for the
currency pair. Assume the order was placed at a moment of high volatility.
It would be possible for the order to be filled at a price significantly lower
than what the trader expected, and thus causing the trader to experience
slippage.
It is noteworthy that after the announcement of big market news,
financial markets often do not move in only one direction. There can be
jumps and long candlesticks for price movement in both directions
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Chapter Four
(Lahaye et al. 2011). It is possible during such news related volatility for
delays to occur in the filling of orders. Even if a trader places an order at
the right time, delays in filling the order can result in the trader incurring
losses. For example, assume that a retail trader placed a long order for a
currency pair at US$1.260, hoping to go short at US$1.270 to make a
profit. Assume there was a delay in the order being filled, then the
currency pair price jumped to US$1.501 where it was filled. Then assume
there was another jump back to US$1.265. Since the long order was filled
at a significantly higher price, the trade was not profitable for the retail
trader.
A retail trader should be mindful of the aforementioned volatility
related risks that are associated with news trading. As a precaution, the
retail trader can opt to use limit orders with target profits to help manage
this volatility risk during periods of high news related volatility.
4.1.7 Heikin-Ashi
Some day traders use Heikin-Ashi charts rather than normal candlestick
charts to identify their patterns. In fact, Heikin-Ashi charts can be used for
crossovers, momentum, and reversals trading strategies. The choice of the
trader to use Heikin-Ashi Charts depends on their tolerance for false
signals. Most brokers offering online trading platforms will have the
option to display price movements as Heikin-Ashi candlesticks.
4.1.8 Elliott Wave Based Trading
As mentioned in Chapter Three, the Elliott Wave Theory can be used
to identify chart patterns. Such patterns can be used to inform decisions to
go long or go short. Consider an example in Figure 4.01. A retail trader
may look at the charts of the XAU/ USD currency pair in July 2018 and
wonder if to buy or sell gold (XAU).
Recall, the rules regarding the Elliott Wave Theory: Wave 2 should not
go beyond the start of Wave 1, and Waves 2 and 4 may frequently bounce
off FRLs. Assume that a trader applied such rules to Figure 4.03. This
application may be reflected in Figure 4.03b.
Trading Strategies
Figure 4.03a: XAU/ USD Currency Pair July 3 – July 5 2018
Source: FX Choice (2018)
Figure 4.03b: XAU/ USD Currency Pair July 3 – July 5 2018
Source: FX Choice (2018)
89
Chapter Four
90
In Figure 4.03b Elliott Waves 1, 2, 3, and 4 all bounce of FRLs. The
2nd and the 4th waves do not exceed the start of Wave 1. Given that Wave 5
was at 23.6% Fibonacci Ratio July 5th 2018, a reversal may occur. If a
reversal occurs, possible support levels are US$1,256 (the 38.2%
Fibonacci Ratio), US$1,255 (the 50% Fibonacci Ratio), or US$1,254 (the
61.8% Fibonacci Ratio).
4.2 Evaluating the Trading Strategy
Traders should evaluate their trading strategy to determine its success,
and where improvement is needed. Such an assessment requires that the
trader records the following information:
x
x
x
x
x
x
the average profit or loss daily;
the size of the average win;
the size of the average loss;
the average risk which is taken per trade;
the win to loss ratio; and
the number of round-trips taken in a day.
A trading strategy can only be evaluated properly only when its profit,
loss, and risk have been measured accurately. The average profit will
indicate the profitability of a retail trader on a daily basis. If the
profitability is low, or if there is a loss, the trading strategy should be
adjusted.
The average size of the win provides insight into the optimal time the
trader is holding the position to closing the trade. Assuming the financial
capital traded is held constant, the size of the winnings can indicate
whether the trader is closing their winning positions too early or not.
Likewise, the size of the average loss also indicates if the trader is holding
losing positions too long. With such information, the trader may amend
their strategy and opt to hold winning positions for a longer period of time.
Also, the may utilize a more stringent risk management strategy to limit
their losses.
As part of the evaluation, a trader could review their trades over the
past day/ week, and ask themselves the following questions:
x Was there a strategy for opening and closing positions? Is so, was it
followed?
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91
x Was any technical or fundamental analysis tools used to inform
trading decisions?
x Was there a target for wins/ losses?
x Were trades closed/ canceled early?
x Were losing positions held longer than outlined in the strategy?
x Did human emotion influence any of the trading decisions?
The answers to the simple aforementioned questions can provide
insight as to why a trader may be experiencing losses.
Of course, more complex methods such as the Sharpe Ratio, and
Monte Carlo simulation can be used to more rigorously assess the trading
strategy of a trader. Such complex strategies may be used by an advanced
trader with a background in financial economics, however, they are
beyond the scope of this book which targets the novice trader.
4.3 Summary Insight
It is difficult for a trader to successfully earn a profit on a long-term
basis with the implementation of an objective and winning strategy. This
chapter first reviewed the basic features that a trading strategy should
contain. These include the entry and exit rules, risk management rules, and
position sizing rules.
Then this chapter explored a number of simple trading strategies.
Crossovers, momentum trading, and reversal trading were identified as the
main strategies. However, they could be supplemented by information
from Moving Average Envelopes, Bollinger Bands, and Heikin-Ashi
charts. While trading strategies may rely on indicators it is important to
note that an indicator is not a trading strategy.
Finally, this chapter considered a basic framework to evaluate the
performance of utilized trading strategies. Simple trading strategies are
relatively easy to build, implement, and evaluate. Conversely, complex
strategies are more difficult and time-consuming to build, test, and
optimize. The same principle applies to evaluation methodologies. As
previously mentioned, this book focused on the simple approaches as the
target audience is the informed reader seeking to increase their financial
knowledge.
The next chapter, Chapter Five, probes risk management in greater
detail as it is a crucial element of a trading strategy.
CHAPTER FIVE
RISK MANAGEMENT
5.0 Introduction
Trading is the practice of trading strategies and managing risk.
Successful traders carefully assess and justify their risk whenever
considering making a trade. In other words, they need to be mindful of the
loss they can make while entering trades. They may intensely use limit
orders to open and close positions so that their trades are executed at target
prices. As a risk management strategy, a trader needs to know when to
enter trades, how long to hold the position, and when the exit the trade.
Such information would be beneficial to a trader as it would prevent them
from buying into a profitable momentum too late, holding a loss position
too long, and selling a profitable position too early.
Retail traders should only trade based on money that they can afford to
lose. This is suggested since there is a potential for the trader to lose their
money from engaging in the practice of trading. Money for essential
consumables such as food, rent, utility bills, educational expenses, health
care, etc. should not be risked by the market participant in trading. In fact,
if the retail trader fears to lose their money they may find themselves
holding profitable positions too short, or selling losing positions too early,
which in turn can result in the trader realizing unnecessary losses. This of
course could result in the retail trader operating a negative profit to loss
ratio. Thus, as a recommended rule, if a person can’t afford to lose the
money that they risk in trading they should stick to demo trading until
their financial position improves.
This chapter considers a number of strategies to manage risk. It
reviews the various types of risk, the optimal point to enter and close
trades respectively, and strategies for position sizing.
Chapter Five
94
5.1 Types of Risk
Market participants on a stock exchange face different risks. These
risks include:
x
x
x
x
x
Market risk;
Liquidity risk;
Concentration risk;
Credit risk; and
Inflation risk.
5.1.1 Market Risk
Market risk is that a market participant incurring a negative return or a
drawdown due to a change in the market. The main market risks are price
risk, interest rate risk, and currency risk.
Price risk is the chance that the price of the asset can go in an
unfavorable direction. For example, if a trader went long on a stock, the
price risk would the chance that the price of the stock declines rather than
increases. Alternatively, if the trader short-sells the stock, the price risk
would be the chance that the price goes up rather than down, resulting in a
loss for the trader. Stock prices are marked to market daily, subsequently,
their prices can change on a daily basis. In fact, stock prices can fluctuate
within a day. Thus, price risk is inherent in all stocks that are public traded
on exchanges.
Another price risk that a trader can face is a stock halt. A market-wide
stock halt is when the price of all the stocks on an exchange is suddenly
frozen. This may result from a technical glitch of the online platform of
several brokers, or a direct intervention of a central authority to freeze the
market. Non-market-wide stock halts can also affect specific stocks. Stock
halts, in general, are risky to market participants, as they can be
accompanied by huge jumps in the stock price at the end of the halt (Lahaye
et al. 2011).73
73
Stock halts are not to be confused with limit moves. Limit moves are limits set
by Exchanges to confine the price movement of assets within ranges. For example,
the daily price of soybeans on an Exchange may be allowed to fluctuate $0.50
above or below the previous day closing price.
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95
Price risk can be addressed with Limit Orders or the utilization of
options. Limit orders are discussed later in this chapter. Options give an
economic agent a right, not an obligation, to partially counter the effects of
adverse price movement by the execution of a strike price. Options can be
a useful tool for investors to hedge against the risk of adverse price
movement.
Interest rate risk is the chance that the market participant can
experience some loss in the value of their asset due to a decline in the
interest rate on the asset. Interest rate risk is relevant to bonds since bonds
have coupons attached to them. However, interest rate risk is not relevant
for stocks since stocks do not bear interest.
Currency risk is the chance that the market participant from country A
trading assets in the currency of country B, may incur some loss due to a
change in the floated exchange rate. For example, on Thursday January 3,
2017, the price of First Citizen’s Bank’s stock (FIRST) was TT $34.98 on
the TTSE. The exchange rate between the US and Trinidad and Tobago
(T&T) on that day TT$6.7563 = US$1. By January 9, 2017, the exchange
rate between T&T and the US depreciated to TT$6.7976 = US$1.
However, the price of FIRST was still TT$34.98. A market participant
from the US trading in TTSE would experience some loss from the
depreciation, even though the price of FIRST did not change.74, 75
5.1.2 Liquidity Risk
Liquidity risk is the risk of the market participant being unable to sell
the asset when they desire. It can also be considered as the risk of the
market participant being unable to sell the asset at a fair price when they
want to liquidate their assets.
74
At the TT$ 6.7563 = US $1 exchange rate, the value of the assets would be
US$5.18 per share. At the TT$6.7976 = US$1, the value of the assets would be
US$5.15 per share. The depreciation would cause the market participant to incur
US $0.03 per share in loss, or a 0.6% downturn.
75
Note: the TTD/ USD currency pair would be considered an exotic rather than a
major currency pair, since the TTD is not traded or demanded in high volumes,
relative to the currencies of major developed countries, or emerging economies
(e.g. Brazil and China). Moreover, T&T’s currency can be also be consided as a
weak currency relative to the currencies of the countries that are relatively large
players in international trade. Futhermore, it is highly unlikely that the TTD would
become a majour currency within the short-term to medium-term.
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Chapter Five
Liquidity risk is a common feature of inefficient exchanges. On the
TTSE liquidity risk is a real issue, as there are some days in which there
may be no trades, even for popular stocks. For instance, between
Wednesday July 27, 2016, and Tuesday August 9, 2016, there were no
trades for FIRST on the TTSE. Thus, a market participant seeking to
liquidate the shares of FIRST over the aforementioned period may find
difficulty in doing so. Liquidity risk may not be an issue on exchanges in
developed countries as the Market Maker would be available to buy or sell
stocks to facilitate liquidity.
5.1.3 Concentration Risk
Concentration risk is the risk that a market participant can incur a large
loss due to too much of their money being invested in one (1) asset, or one
(1) type of asset. For example, assume that an investor purchased only
United Continental Holdings Inc. (UAL) stocks prior to April 9, 2017. On
April 9, 2017, an incident occurred in United Airlines whereby a
passenger was forcibly removed from the airplane and sustained injuries
(Bowerman and Aulbach 2017). The incident attracted negative publicity
worldwide, causing the stocks to United to decline (Reklaitis 2017). On
April 7, 2017, UAL was US$70.88 per share. However, by April 13, 2017,
UAL closed at US$69.07 per share. Thus US$1.81 was lost from the
market value of United’s stock over the trading week. The investor
holding only UAL would lose 2.5% of the value of their portfolio.
However, if the investor held other stocks in addition to UAL, once the
value of the other stocks didn’t decline, the investor would experience less
than a 2.5% loss to their portfolio.
The financial economics literature has long recognized concentration
risk (Wagner and Lau 1971; Lee and Lerro 1973; Merton et al. 1978;
Lütkebohmert 2008). In fact, modern portfolio theory (MPT)76 attempts to
address concentration risk.
In other words, if the economic agent had 1 asset and the returns from
that one asset were negatively affected, then the economic agent would
lose from holding that individual asset. However, if an economic agent
76
MPT is a financial economics theory that explains how a risk adverse investor
can minimize their concentration risk of their investment by constructing
portfolios. The portfolio, which is a group of assets, allows the market participant
to earn a given level of return, while minimizing their concentration risk
(Markowitz 1952).
Risk Management
97
holds a portfolio of different assets, it is possible even if 1 or more assets
in the portfolio are performing poorly, the overall portfolio may still
perform well since the weight or contribution of any 1 asset to the
portfolio may be small. Thus, concentration risk is addressed by
diversification and the construction of portfolios.
It is a common misconception that higher risks will generate higher
returns. High risks may theoretically provide a probability of a higher
return. However, it is not guaranteed to occur. In fact, higher risk can
result in higher losses.
The tradeoff between risk and return can be displayed graphically via
the Efficient Frontier. The Efficient Frontier shows the various returns a
market participant can earn given various risk. In Figure 5.1, the Efficient
Frontier is the line that displays the maximum return that a market
participant can acquire for a given level of risk.
A trader seeking to avoid concentration risk by developing a portfolio
should aspire for a portfolio that is on the Efficient Frontier. All portfolios
below the Efficient Frontier reflect inefficiency as the market participant
can earn a higher return for the associated risk. All points above the
efficient frontier reflect combinations of risk and returns that are
unattainable for the market participant.
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98
Figure 5.1: Efficient Frontier
Source: adapted from Benninga and Czackes (2000)
5.1.4 Credit Risk
Credit risk is the risk that the economic agent that has received credit
would not be able to repay in the future. In the context of exchanges, credit
risk is the risk that the government or company which issued a fixedincome security, such as a bond, would not be able to repay at maturity.
The credit risk is the risk that the government or company would default
on the bond at maturity.
Both traders and investors trade bonds and fixed-income securities. In
instances where governments default on bonds, the government may
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99
negotiate debt restructuring with the bondholders. This may involve the
granting of haircuts on the bond, and the extension of maturity.
Bondholders refusing to accept haircuts77 may holdout on the bond
restructuring, and in worst case scenario raise a ligation matter on the
government with an international country.
5.1.5 Inflation Risk
Inflation risk is the risk that the profitability of investments is eroded
by inflation. Inflation erodes the purchasing power of money over time.
Inflation risk is relevant for medium-term and long-term investments, as
the inflation can reduce the real value of the return on the investment over
time.
There are other risks that market participants face on stock exchanges.
For instance, a market participant from a developed country purchasing
securities in a developing country may face some political risk if the
government of the country decides to nationalize certain industries,
especially without compensating foreign owners.
5.2 When to open a Position
When entering trades, a trader should determine the optimal point to
make an entry position. As previously mentioned, there should be some
preconditions that have been met which provide a trader with the
opportunity to make a profit.
For example, assume that the price of a stock is currently $20 per
share. Assume that the trader expects that the price of the stock to rise to
$40 per share within the next 30 minutes, then decline to $20 per share. In
such case, the trader should enter the position at $20, wait for the price to
rise to $40, and then exit the position.
In the alternative scenario where the price of the stock is $40 per share
and the trader anticipates the decline to $20 per share, a profit can be made
by short selling. The trader could short sell the stock at $40, and then when
the price declines they could close the position to cover.
77
A haircut is a discount on the par value of a bond. It is typically negotiated
between creditors and debtors that have defaulted or on the verge of default.
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Chapter Five
Ideally, the optimal entry point is the position that allows the trader to
maximize the expected profit. This would be the lowest price for the
opportunity where a trader can make a profit from going long. Likewise, it
would be the highest price for the opportunity where the trader can earn a
profit from short selling.
Some examples of entry positions include:
x If the 5-day EWMA crosses from below to above a 20-day EWMA
go long, or if the 5-day EWMA crosses from above to below the
20-day EWMA go short;
x If the RSI close below 20 to go long, or if the RSI to rise above 80
to go short;
x If the daily close is higher than the weekly close by 5% then go
long, or if the daily close is lower than the weekly close by 5% then
go short;
x If the present day’s close is higher (lower) than the previous 3 days
close, as there was an increase in the trading volume over the past 3
days, then go long (short); and
x If the price of a stock goes outside of the Bollinger Bands then go
long is resistance is broken, or go short if support is broken.
Traders should use multiple criteria in an entry filter to confirm market
patterns before entering trades.
5.3 When to close a Position
After a trader has entered a position, they need to determine the
appropriate point to close the position.78 Any trader can enter a position.
However, profits or losses are made when the position is closed. If the
position is not closed at the appropriate point in time, then profits that
were earned could be lost. Furthermore, if the trader anticipated the market
wrong, a strategy is required to minimize their loss and move on.
A successful trader should have rules for an exit position. There are
three exit rules which can be used to minimize losses and protect gains.
They are:
78
If a trader went long on the open position, the close position would be to go
short. Also, if the trader went short on the open position, the exit position would be
to go long.
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101
x Stop-Losses to protect the capital of the trader;
x Profit-Stops to when gains are realized; and
x Time-Stops to exit positions when the market is not moving.
A stop-loss is a limit order that is used to limit the loss a trader may
incur when the market moves in an unfavorable direction. It allows the
trader to close the position and reduce their loss without allowing the
market from going too far in the unfavorable direction.
As a strategy to minimize risk, a trader can use the current level of
support as the stop-loss position. If the trader anticipates the market wrong
and the stock moves in the wrong direction and breaks support, then the
loss is minimized at support, and the trader may move on.
If support is used to determine the stop-loss, then the trader may use
Fibonacci Retracement Levels to identify potential support levels. Recall,
a rule for the Elliott Wave Theory trading strategy is “Wave 2 should not
go beyond the start of Wave 1, and Waves 2 and 4 may frequently bounce
off FRLs.” The FRL can be used to identify possible levels of support. The
stop-loss could then be set at such price.
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Figure 5.2: XAU/USD July 5, 2018 – July 6, 2018
Source: FX Choice (2018)
For example, consider Figure 5.2 which illustrates a case where FRL
has been applied to XAU/ USD.79 The closing price in Figure 5.2 was
US$1,258.20. If a reversal occurs, possible support levels are US$1,256
(the 38.2% Fibonacci Ratio), US$1,255 (the 50% Fibonacci Ratio), or
US$1,254 (the 61.8% Fibonacci Ratio). Thus, the retail trader may set
their stop-loss at one of the FRL levels.
The stop-loss can be specified as a fixed dollar amount. For example,
assume that the price of a stock A is $20 when a trader goes long. Assume
79
Note: XAU is the ticker for gold. Although XAU/USD is not a currency pair,
gold and several other commodities are traded on forex markets just like any other
currency pair.
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103
that the stop-loss is identified at $19. Thus, if the market goes in the
opposite direction that the trader anticipates, then the maximum loss the
trade incurs on the trade is $1.80
The stop-loss can also be specified as a percentage of the market price,
or a percentage of volatility. For example, assume that after the retail
trader went long on a stock at $30, then decided to implement a 5% stoploss. Five percent of $30 is $1.50. Then, then they would set the stop-loss
at $28.50. In fact, trailing stops are percentage stop-losses. Trailing stops
are effective as the stop-loss position changes as the market moves in the
favorable direction. For example, assume the trader went long at $30 and
implemented a 5% stop-loss. Assume the price of the stock increased to
$50. The stop position would be adjusted to $47.5. Therefore, as the spot
price suddenly declines after hitting a new resistance level, the trader
would automatically exit the position while earning some profit.81
Consider another scenario, assume the trader wanted to implement a
stop-loss at 50% of the market volatility after going long at $30 per share.
Assume that the standard deviation, which is typically used as a measure
of volatility, was $10 for that day. Then 50% of the market volatility
would be 50% of $10, which equates to $5. Thus, the trader would
implement a stop-loss at $25.
Once the stop-loss has been identified, the trader can similarly
establish a stop position for their profit. The trader should calculate the
stop profit position based on their profit-loss ratio82. The stop profit
position would be the price in which the trader may automatically close
the position once the target profit level is achieved.
For example, in the example where the price of a stock A is $20, and
the trader identified a $19 stop-loss, if the trader has a profit-loss ratio of
80
This is the loss the trader would make, excluding the cost of commission for the
broker.
81
Note: This is one of main reasons why limit orders should be used to minimize
risk. It allows the trader to automatically lock in traders based on the direction of
the market. If only market orders are used to facilitate trades, then a risk adverse
trader would have to consistently monitor the market without leaving their
computer to manually execute trades when the market changes.
82
The profit-loss ratio is the ratio of the profits to loss that a trader makes. If the
profit-loss ratio is 2:1, then for every $2 the trader earns in profit, they lose $1.
Thus, even if the trader takes the correct position on at least 50% of their trades
they will still be profitable.
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Chapter Five
2:1, then their target profit would be $2. Therefore, they would desire that
the stock price increases to $22 to execute their stop profit order.
If the trader is risking $100 per trade but can earn $300 in profit, then
they have a 3:1 profit=loss ratio. However, if the trader is risking $100 per
trade, but can only make $10 profit, then they have a 1:10 profit-loss ratio.
Such setup is unlikely to be profitable on a long-term basis as it would
require a trader to be accurate about the market direction at least 90% of
the time in order to break even.
Many new traders may desire to earn large profits in just one or a few
trades. However, the key to success is to earn profits consistently. This
may involve the earning of a series of small profits, which add up over
time.
It is important to note that traders should also ensure that they close
their stop order whenever they cancel or close their position. If they don’t
perform such action after making profits from a winning position, then
when the market turns in an unfavorable position the order will be filled.
This could result in the trader making unnecessary losses.
Time stops are stop orders that are related to time. The trader
implements an order to close a trade, or the close a certain percentage of
an order after a certain period of time passes. Time stops are implemented
regardless of if the trader profit target is achieved or not. Time stops are
useful for traders when markets are not moving.
5.4 Position Sizing and Balancing Risk
Successful traders balance their risk. Consider the following scenario, a
trader performed a series of fundamental and technical analysis to
determine what stocks to trade. Assume the trade took to correct entry and
exit positions on the first nineteen (19) of their trades. On their twentieth
trade, they took the wrong position. However, as they were investing
100% of all their trading capital in each trade, the twentieth (20th) trade in
which they make a loss, they will lose all of their earnings.
Such a scenario reflects a trader with a poor strategy to manage risk.
Regardless of how much earnings they made previously if they risk all of
their earnings in each trade, then the one time in which the trader takes the
wrong position, they risk losing everything.
Risk Management
105
Subsequently, a trader should only risk a percentage of their entire
account on each trade. The percentage will vary depending on the risk
tolerance of the trader. A risk adverse trader would only risk a small
percentage of their account on each trade. A trader with a higher risk
tolerance will risk a larger percentage of their account in each trade.
Position sizing determines the amount of trading capital the market
participant risks with every trade. In the example where the trader risks
100% of their trading equity in each trade, their risk was not balanced
properly. Although the position sizing would be limited by a market
participant’s trading capital, it is still possible to set a target as to how
much capital should be risked with each trade.83
This book considers 5 objective approaches to determine the position
size. They are:
1. Volatility Adjusted;
2. Martingale;
3. Anti-Martingale;
4. Fixed Sum; and
5. the Kelly Method.
Volatility Adjusted Position Sizing specifies the number of shares per
trade as a fixed percentage of trading capital divided by the trade risk.
Consider an example, assume that the trader had a risk size of 3% of
equity, a risk per contract of $100, and an account size of $25,000.
The Total Equity to Risk = $25,000 × .03 = $750
Number of Contracts = $750/ $100 = 7.5
Thus, the trader utilizing the volatility adjusted position sizing
technique would only take 7 contract positions.
Consider another example where a trader had a smaller account of only
$2,500. If a 3% risk per equity is assumed, then only $75 would be risked
83
More sophisticated methods can be used to determine the optimal position size
for different assets. For instance, in the case of futures, the optimal hedge ratio
could be used to determine the optimal amount of futures to be held to offset the
spot position to minimize the basis risk to the portfolio. Such advanced techniques
are not considered in this book.
Chapter Five
106
on each trade. Thus, regardless of the share price, the trader will only
spend $75 on each trade.
The Martingale Position Sizing Rule is a gambling rule that doubles
the size of each trade after each loss and but retains the unitary position
after each win (Parado 2011).
The Anti-Martingale is a variation of the Martingale Rule. It
recommends the doubling the number of trading units after each win but
retains the unitary position after each loss.
The Fixed Sum Position Trade Rule is where the same size equity is
used for each trade. For example, a trader with a small account of $1,000
may risk only $100 per trade.
The Kelly method utilizes a formula to determine the optimal position
sizing. It is given by
‫ ݕ݈݈݁ܭ‬ൌ
ሺௐ௜௡Ψି௅௢௦௦Ψሻ
ሺ஺௩௘௥௔௚௘௉௥௢௙௜௧Τ஺௩௘௥௔௚௘௅௢௦௦ሻ
(5.01)
For example, assume a trader’s strategy wins 55% of the time, has an
average win of $350, and an average loss of $125. The Kelly percent
indicates that the 3.57% of the total trading capital should be risked on the
next trade.84
The aforementioned position sizing methods may not produce the
optimal position size for every trader or for every strategy. To more
accurately fine tune the trading position sizing would require more
complex tools, historical returns, and econometric models to assess the
empirical performance of the strategy. Researchers have come to accept
that financial markets have a non-Gaussian distribution (Lo et al. 1988;
Campbell et al. 1997; Embrechts et al. 2002). Furthermore, some
researchers have come to accept the fractal distribution of financial
markets (Peters 1994; Mandelbrot and Hudson 2010; Mandelbrot 2013).
Such key non-Gaussian assumption suggests that non-linear, regimechanging econometric models are more relevant for the assessment of
position sizing. However, such complex modeling is outside the scope of
this book.
84
Kelly % = (55-45)/(350/125)
Kelly % = 10/2.8
Kelly % = 3.57%
Risk Management
107
It is important to note, when trading shares, a trader seeking to earn a
profit need to trade sufficient shares in order to cover the cost of the round
trip. The cheapest most brokers will charge for a trade is $5. Thus, the cost
of the round trip is $10. If a trader expects the target gain from a trade to
be only $1, then the number of shares the trader must trade in order to
break even is 10. The following equation outlines the number of shares a
trader must trade in order to break even
ܰ‫ ݏ݁ݎ݄ܽݏ݂݋ݎܾ݁݉ݑ‬ൌ
்௔௥௚௘௧௣௥௢௙௜௧
௖௢௦௧௢௙௧௛௘௥௢௨௡ௗ௧௥௜௣
(5.02)
Thus, if the price of the share is $40 per share, and the target profit is
$0.50 per share, then the trader must trade 20 shares, and risk $800 of their
trading capital in order to break even.
5.5 Common Mistakes
Traders that find themselves in a losing position often make a number
of mistakes. Some of the more common mistakes include:
x Trading without a strategy;
x Trading stocks based on emotion rather than technical or
fundamental analysis;
x Failing to manage risk;
x Entering positions too soon;
x Closing positions too late;
x Holding losing positions too long; and
x Missing changing trends, reversals or news
5.6 Summary Insight
The cardinal purpose of risk management is to curb losses to trading
capital. This chapter examined the various risks that market participants
face in financial markets. Market risk emerges as one of the more
prevalent risk that economic agents face on markets. In fact, price risk will
be faced by every trader.
Due to price risk, traders may adopt a number of measures to mitigate
losses. This chapter identifies stop orders as a very useful tool to limit
losses in the event of unanticipated adverse price movement. Fixed dollar
amount stop-loss, Volatility-Adjusted Stop-Loss, and Trailing Stops can
all be used by a trader to limit potential loss.
108
Chapter Five
Concentration risks may be addressed by market participants creating a
portfolio of assets to limit the exposure to adverse price movement.
Furthermore, risk exposure can also be reduced by the incorporation of
position sizing rules in the trading strategy. This chapter highlighted a
number of simple position rules. The trader’s choice of position sizing
rules would depend on their risk tolerance, their preference for complexity,
and size of their trading capital.
Given that the main tenants of a trading strategy have been discussed,
Chapter Six will assess the average trading day of a trader.
CHAPTER SIX
THE AVERAGE TRADING DAY
AND GENERAL CONCLUSION
6.0 Introduction
The previous chapters reviewed the basic Technical Analysis tools, and
strategies. Given such information, the retail trader will have to decide
which combination of Technical Analysis tools to use.
This chapter highlights the importance of an objective trading strategy
used by a retail trader. Moreover, a mechanical trading system should be
implemented by retail traders seeking to systematically acquire more gains
than losses. This chapter also presents an example of a mechanical trading
strategy that a retail trader can implement for stocks, and another for
currency pairs based on Technical Analysis.
6.1 Mechanical Trading Systems
Mechanical trading systems are objective systems based on the
recognition of patterns of charts, and values of indices and oscillators,
which in turn could be used to inform appropriate trades for a retail trader
to take. Such trading systems are referred to as ‘mechanical’ since they
inform potential trades without taking into consideration human emotion.
Many websites claim to have a mechanical trading system that
generates profits. Usually, they require a market participant to pay a fee to
use their system. Many of these mechanical trading systems actually do
work. That is because they are based upon a specific set of trading rules
which the system follows without any emotion. Many retail traders can
make the same profit from implementing a system, but the fail to do so
since their emotions cause them to break their trading strategy. They lack
the discipline to trade in an emotionless systematic manner.
Rather than paying hundreds or thousands of dollars to use a
mechanical trading system, it is possible for a trader to create their own
Chapter Six
110
mechanical trading system for free. The thousands of dollars which would
have been spent as a membership fee to use a website’s mechanical trading
system could be used as trading capital for the retail trader.
A retail trader that is developing their own mechanical trading system
should aspire to achieve two very important goals:
1. Their system should be able to identify trends as early as possible.
2. Their system should be able to avoid you from getting
whipsawed85.
If their system can accomplish the aforementioned goals with they will
have a much better chance of being a successful trader than a market
participant that trades with absolutely no strategy. Notwithstanding, the
achievement of such goals is difficult as they contradict each other. A
system which is designed to identify trends very early is likely to pick up a
lot of false signals. This, in turn, can result in retail trader being misled by
trading in the wrong direction. Likewise, a system that focuses on
avoiding whipsaws will rely on lagging indicators to confirm patterns.
This could result in the retail trader missing out on excellent opportunities
to earn financial gains from the market. Thus, a retail trader is tasked with
the responsibility of finding a balance between a system that identifies
trends early, and a system that would eliminate false signals.
Anyone that understands the basic principles behind Technical
Analysis can develop a mechanical trading system. While it does not take
long to develop a mechanical trading system, it does take time to
thoroughly test the system and verify that it produces more gains than
losses. A working mechanical trading system can be developed in a
number of steps.
Step 1: The Time Frame
This first thing that a retail trader should consider when developing a
mechanical trading system is what type of trader they are. As mentioned in
Chapter One, the main trading styles include: position trading, swing
trading, scalping, and day trading. Day traders and scalpers tend to hold
positions shorter than position traders and swing traders. Thus, they (the
85
A whipsaw refers to a specific movement of an asset’s price. It refers to a
situation where an asset’s price is moving in one direction but then quickly pivots
and moves in the opposite direction.
The Average Trading Day and General Conclusion
111
day traders and scalpers) would need to look at charts on a regular basis.
In fact, they would need to review intra-day charts, such as the 1-minute
chart, 5-minute chart, 15-minute chart, etc. This need to visualize shortterm charts is driven by the fact that large price changes can occur for
some assets within very short periods of time. In fact, it is possible for an
asset to experience over 50% change in price within a minute. Such jumps
can be very profitable for retail traders that manage to trade in the correct
direction before the jump occurs, while they can generate large losses for
retail traders than have open positions on the wrong side of jumps.
Step 2: Utilizing Technical Analysis Indicators
Mechanical trading systems should also utilize Technical Analysis
indicators. The indicators are very useful in identifying trends. Some of
the popular Technical Analysis indicators which can be used include
Moving Averages, Bollinger Bands, the RSI or the Stochastic Oscillator,
the Force Index, and Fibonacci Retracement Levels. The Mechanical
trading system may involve a strategy that utilizes the Technical Analysis
indicators and recommends specific actions when certain conditions are
met. For example, if a 5-day Moving Average crossover a 20-day Moving
Average, and the RSI is below 20, the retail trader could use such
conditions as a rule to go long on the asset.
Step 3: Incorporate Risk Management
Recall, Chapter Five emphasized that risk in embedded in the trading
of financial assets. There is always the possibility that things do not turn
out as how the market participant anticipated, resulting in a loss.
Successful traders are the retail traders than manage to implement an
effective strategy to minimize their loss. This can be done by
implementing rules for the entry and exiting of positions. For example, a
trailing stop could be implemented with every order, such that if there is
an unexpected change in the price of an asset by 10%, the stop-loss will be
automatically triggered to close the position. Risk can also be managed
with position sizing. For example, the retail trader may only trade forex
with trading factors no greater than 0.05, or they can spend no more than
US$100 on each stock trade.
Step 4: Back-Testing
After specifying a mechanical trading strategy, a retail trader should
write down or record the rules. They should also diligently follow their
mechanical trading strategy. To verify the robustness of a mechanical
Chapter Six
112
trading strategy a retail trader should back-test the strategy will real
historical data. The retail trader can also opt to test a strategy on a demo
account before proceeding to live trading.
6.2 The Average Trading Day for the Informed Stock
Trader
Just after market open, there may be high trading volume, and high
liquidity. The informed trader should already have a mechanical trading
strategy ready to direct them about how to trade. Before entering the
market, the informed trader should have a number of tools:
x Stock Scanners (e.g. Yahoo Finance, Finviz, Stock Twits, or Trade
Ideas);
x Stock News (e.g. Yahoo Finance, Trade Ideas, chat rooms);
x Charts (e.g. Finviz, eSignal); and
x Broker (e.g. FXchoice, SureTrader).
The retail trader should start by going to a stock scanner. Traders
should consider low float stocks, with high price movements in either
direction. Traders may consider stocks with at least 10% change in price.
Free scanners such as Yahoo Finance, and Google Finance are excellent
for identifying the top movers in a market.
Stock scanners should also be used to identify chart patterns. Finviz is
an excellent free scanner to reveal chart patterns. Trade Ideas can be used
by a trader willing to pay for its patterns.
As a recommendation, a retail trader intending to trade on momentum
can look for the following patterns for up-trends:
x Rising Wedges;
x Rising Rectangles; and
x Bull Flags.
For down-trends, the trader may look for the following patterns:
x Falling Wedges;
x Falling Rectangles; and
x Bear Flags.
The Average Trading Day and General Conclusion
113
The retail trader should confirm the chart pattern by the reviewing of
news. Good news should justify bullish movement, while bad news should
be associated with bearish movement.
On the online platform, the trader can review the level 2 data to acquire
information on relative volume. If the trader is using Finviz free services,
it can receive information about the overall relative volume from the
previous day. If the trader pays for Finviz services, they would be able to
access Finviz’s intraday charts. Finviz also provides information about a
stock’s RSI, indicating if it is overbought or over-sold.
Retail traders using the moving average crossover strategy may also
acquire the relevant price information from Yahoo Finance or Finviz.
The retail trader can also briefly search stock scanners such as Yahoo
Finance and Google Finance for news regarding the stock. Once the trader
is confident about the emerging pattern, they may then search for an ideal
entry position. The entry position would depend upon the retail trader’s
preference and strategy. For example, a retail trader may set the entry
position for an upward momentum strategy as the second green 1-minute
candlestick after the market opens, once the previous day had a bullish
chart pattern, a relative volume greater than 2, a low float, and positive
news for the stock.
Recall, profits or losses are made only when a position is closed. The
informed trader should have a strategy to manage risk. They may use a
position sizing rule to determine how much trading equity is risked per
trade. Furthermore, they should set target profits. Once the target profit is
made they may keep the position open, however, they may close the
position after the first pullback of a 1-minute candlestick. With regards to
losses, they can initially set a stop loss at 5% lower than their entry price.
The trader may engage in a few trades, or complete round trips within
the morning period. After the trader completes their trading for the day
they may review their profits, losses, and their trading strategy. They may
consider ways to improve the returns of their trading strategy.
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Chapter Six
6.3 A Practical Mechanical Trading System for Trading
Currencies
The currency trader may trade based on Technical Analysis. One
possible strategy involves the use of Bollinger Bands, and the Force Index.
The following rules may be applied.
1. If the Force Index is positive, and moving up and the Bollinger
Bands are trending upward, then the trader may go long with a
position size of 0.10. This pattern must be in both the 1-minute and
the 30-minute candlesticks.
2. If the Force Index is negative, and moving down while the
Bollinger Bands are also trending downward, then the trader may
go short with a position size of 0.05. The same pattern must be in
both the 1-minute and the 30-minute candlesticks.
3. The smaller position size is suggested due to the risk of the broker
closing the position if the trade goes wrong. Furthermore, a stop
loss up to $5 can be applied by the trader. While the target profit
may be $10.
4. If the Bollinger Bands and the force index point in different
directions, then it is deemed a risky trade. The cautious trader may
not place an order larger than 0.01. In such a case, the trade
direction should be taken from the price of the currency pair in both
the 1–minute and 30-minute candlesticks.
5. If the force index is in a bullish divergence, and the RSI is lower
than 20, then it suggests that the currency pair is over-sold and a
bottom reversal may occur. If the Force Index is in a Bearish
Divergence, and the RSI is higher than 80, then it suggests that the
currency pair is overbought and a top reversal may occur.
6. If the 1-minute and the 30-minute candles are indicating different
patterns, the trade may also be deemed risky.
7. If the force index is small and close to 0, the risk adverse trader
should not enter a position. It means there is a weak price change
and volume is weak. Furthermore, the current candlestick should
look like a doji.
8. The trader should not trade during weak volatility since they need
volatility to cover the bid-ask spread and the commission. Thus, the
trader should seek to trade where there is wide Bollinger Bands.
The aforementioned strategy is just an example of how a trader may
create a strategy based on technical indicators. There is no one strategy
The Average Trading Day and General Conclusion
115
that a trader has to use. A trader can develop their own strategy based
upon a combination of technical indicators that they prefer. Furthermore,
the trader’s preference for risk will also influence how they choose to
manage their risk.
Of course, in order to derive the ideal strategy that consistently
generates profits, a retail trader would need to evaluate the winnings and
losses of previous strategies, and make amendments until they derive the
strategy that bests work for them.
6.4 Trading Plan
To be successful at trading, the market participant should have a
trading plan. The plan should be an objective strategy which has been
proven to consistently produce more financial wins than financial losses. If
a retail trader performs poorly at trading, even after being informed about
the fundamentals of financial markets it may be due to one of only two
reasons: either there’s a problem in the trading plan or the retail trader is
not sticking to their trading plan. If the retail trader is trading without a
plan, then they may unable to determine what they are systematically
doing what is right from what is wrong. Thus, the trader may have no way
to systemically correct their previous errors in trading. It is analogous to
the proverbial saying “if you fail to plan you will plan to fail.” A trading
plan doesn’t guarantee success. However, its performance can be
evaluated, and modified to eventually help the retail trader achieve success
on the market.
A trader can make an occasional winning trade while disregarding their
trading plan. This can generate short-term satisfaction, but consistently
entering trades haphazardly can adversely influence a trader’s ability to
maintain discipline in the long term. Trading can be considered as being
analogous to running a marathon, as it requires long-term discipline to a
trading plan to consistently generate an overall positive return in the long
term. Successful traders achieve such success simply by getting the law of
averages to work in their favor over the long run.
In order to build a trading plan, the retail trade should develop a
strategy that suits their personality, their preference for various technical
tools, and their tolerance for risk. The practice of trading strategies which
are not compatible with the market participant’s profile and personality
will drastically lower their chances of achieving success. For example, a
trading strategy which involves the risking of a lot of trading capital with
116
Chapter Six
each trade may not be very successful for a trader that is relatively risk
averse. When the trader sees that a trade is in a high loss they may be
tempted to implement a stop loss and prematurely close an order, even
though the trade may turn profitable if the market participant were to hold
the position for a bit longer.
For this reason, every trader should develop their own trading plan and
strategies. The actual strategies (e.g. crossovers, news/ event trading, etc.)
should be part of a larger plan which specifies what course of action for
the retail trader to take when faced with different scenarios. Thus, a
trading plan and strategies that may be successful in generating profits for
one retail trader may not be profitable for another retail trader.
6.5 Conclusion
Many people enter financial exchanges to trade stocks, forex, and other
financial assets without first being educated about the fundamental
principles behind such markets. The uninformed trader is not cognizant
about how to use the wide range of tools that are provided to them by their
broker. Subsequently, such market participant trades on the basis of
emotion, their preferences, and other subjectivity.
This book provided an introduction to day trading. It begins by making
the distinction between trading and investing. It also elaborates on various
trading styles. This book also informs a reader about how to open an
account for trading stocks or trading forex, factors to consider before
deciding to choose to trade stocks or forex, and how to find stocks to trade.
As Technical Analysis is a very useful technique to inform trading, this
book explains the basic principles of Technical Analysis in detail. The
Technical Analysis tools considered, such as candlesticks, candlestick
charts, Moving Averages, Bollinger Bands, the Force Index, and Fibonacci
Retracement Levels are very popular among successful retail traders.
Success in trading is achieved by implementing a mechanical trading
system incorporated into a wider trading plan. Such an approach takes the
subjectivity away from trading, and allows a retail trader to systematically
generate more financial gains than losses over the long-term. Since risk is
inherent in the practice of trading, this book strongly recommends that a
retail trader should implement an objective strategy to manage and
minimize risk.
The Average Trading Day and General Conclusion
117
Before trading will real money, this book recommends that a retail
trader should trade on a demo account. This would provide a retail trader
to test a mechanical trading strategy, and determine its effectiveness.
Furthermore, through demo trading, the retail trader can become familiar
with a broker’s platform, and can become accustomed to opening and
closing market and limit orders while the financial market is open. Only
after demonstrating success in a simulated environment, should a retail
trader proceed to the market to live trade with real money.
REFERENCES
Bauwens, Luc, Walid Ben Omrane, and Pierre Giot. 2005. “News
Announcements, Market Activity and Volatility in the Euro/Dollar
Foreign Exchange Market.” Journal of International Money and
Finance 24(7): 1108-1125.
Benninga, Simon, and Benjamin Czaczkes. 2000. Financial Modeling.
Massachusetts, United States: MIT Press.
Blinder, Alan S. 1996. “The Role of the Dollar as an International
Currency.” Eastern Economic Journal 22(2): 127-136.
Bowerman, Marry, and Lucas Aulbach. 2017. “United Airlines under fire
after man is dragged off overbooked flight.” USA Today Network,
April 10. Accessed April 15, 2017.
https://www.usatoday.com/story/travel/nation-now/2017/04/10/unitedunder-fire-after-man-dragged-off-overbooked-flight/100287740/
Box, George EP, and G. M. Jenkins. 1976. Time Series Analysis:
Forecasting and Control. 2nd Edition. San Francisco, United States:
Holden-Day.
Brooks, Chris. 2008. Introductory Econometrics for Finance. New York:
Cambridge University Press.
Campbell, John Y., Andrew Wen-Chuan Lo, and Archie Craig MacKinlay.
1997. The Econometrics of Financial Markets. New Jersey, United
States: Princeton University Press.
Colgan, Paul. 2016. “The wild rise in Nintendo shares on 'Pokémon GO'
only makes sense if half of all humanity has the app.” Business Insider,
July 22. Accessed July 25, 2016.
http://www.businessinsider.com.au/nintendo-share-price-rise-onpokemon-go-rationale-2016-7
Charles, Riley. 2016. “Nintendo Suffers 'Pokemon Go' Reality Check
Shares Dive 18% after Profit Expectations Released.” WMUR, July 25.
Accessed July 25, 2016.
http://www.wmur.com/money/nintendo-shares-plummet-18-afterpokemon-go-reality-check/40865718
Elliott, Ralph Nelson. 1938. The Wave Principle. New York: Selfpublished.
Embrechts, Paul, Alexander McNeil, and Daniel Straumann. 2002.
“Correlation and Dependence in Risk Management: Properties and
Pitfalls.” Accessed April 23, 2017.
120
References
ftp://ftp.sam.math.ethz.ch/pub/risklab/papers/CorrelationPitfalls.pdf
4exanalysis. 2016. “Basic Patterns.” 2016. Accessed April 9, 2016.
https://4exanalysis.wordpress.com/category/education/basic-patterns/
Forrest, Jeffrey Yi-Lin, Yirong Ying, and Zaiwu Gong. 2018. “Where Will
the US Dollar Go?” In Currency Wars, edited by, Jeffrey Yi-Lin
Forrest, Yirong Ying, Zaiwu Gong, Guosheng Zhang, and John
Golden, 501-526. Berlin, Germany: Springer.
Forrest, Jeffrey Yi-Lin, Yirong Ying, Zaiwu Gong, Guosheng Zhang, and
John Golden. 2018. “Steepest Optimal Policies for Regulating Capital
Flows and Exchange Rates.” In Currency Wars, edited by, Jeffrey YiLin Forrest, Yirong Ying, Zaiwu Gong, Guosheng Zhang, and John
Golden, 389-407. Berlin, Germany: Springer.
Fratzscher, Marcel. 2009. “What explains Global Exchange Rate
Movements During the Financial Crisis?” Journal of International
Money and Finance 28(8): 1390-1407.
Freedman, David A. 2009. Statistical Models: Theory and Practice.
Cambridge, United Kingdom: Cambridge University Press.
FX Choice. 2018. “Live Account.” Accessed July 5, 2018.
https://my.myfxchoice.com/webterminal/mt4
Global News Wire. 2016. “Sky Solar Holdings, Ltd. Reports Fourth
Quarter and Full Year 2015 Unaudited Financial Results.” Global
News Wire, March 30. Accessed April 3, 2016.
https://globenewswire.com/news-release/2016/03/31/824290/0/en/SkySolar-Holdings-Ltd-Reports-Fourth-Quarter-and-Full-Year-2015Unaudited-Financial-Results.html
Investopedia. 2006. “What is a ‘Reversal’?” Accessed April 8, 2016.
http://www.investopedia.com/terms/r/reversal.asp
—. 2016. “Electronic Communication Network (ECN).” Accessed April
14, 2017. http://www.investopedia.com/terms/e/ecn.asp
—. 2017. “Mark to Market – MTM.” Accessed April 15, 2017.
http://www.investopedia.com/terms/m/marktomarket.asp
Janssen, Cory, Chad Langager and Casey Murphy. 2006. “Technical
Analysis: Chart Patterns.” Investopedia. Accessed April 14, 2017.
http://www.investopedia.com/university/technical/techanalysis8.asp
Lahaye, Jérôme, Sébastien Laurent, and Christopher J. Neely. 2011.
“Jumps, Cojumps and Macro Announcements.” Journal of Applied
Econometrics 26(6): 893-921.
Lee, Sang M., and A. J. Lerro. 1973. “Optimizing the Portfolio Selection
for Mutual Funds.” The Journal of Finance 28 (5): 1087-1101.
Levin, Ginger, and John Wyzalek. 2014. Portfolio Management: A
Strategic Approach. Florida: Auerbach Publications
A Practical Introduction to Day Trading
121
Lo, Andrew W., and A. Craig MacKinlay. 1988. “Stock Market Prices Do
Not Follow Random Walks: Evidence from a Simple Specification
Test.” Review of Financial Studies 1(1): 41-66.
Lütkebohmert, Eva. 2008. Concentration Risk in Credit Portfolios. Berlin,
Germany: Springer Science & Business Media.
Mandelbrot, Benoit B. 2013. Fractals and Scaling in Finance:
Discontinuity, Concentration, Risk. Berlin, Germany: Springer Science
& Business Media.
Mandelbrot, Benoit B., and Richard Hudson. 2010. The (mis) Behaviour of
Markets: A Fractal View of Risk, Ruin and Reward. London, United
Kingdom: Profile Books.
Markowitz, Harry. 1952. “Portfolio Selection.” The Journal of Finance
7(1): 77-91.
Merton, Robert C., Myron S. Scholes, and Mathew L. Gladstein. 1978.
“The Returns and Risk of Alternative Call Option Portfolio Investment
Strategies.” Journal of Business 51 (2): 183-242.
Mitchell, Jason. 2001. “Clustering and Psychological Barriers: The
Importance of Numbers.” Journal of Futures Markets: Futures,
Options, and Other Derivative Products 21 (5): 395-428.
Morris, Gregory. 2006. Candlestick Charting Explained (3rd Edition).
New York: McGraw-Hill.
Nag, Anirban and Jamie McGeever. 2016. “Foreign exchange, the world's
biggest market, is shrinking.” Reuters February 11. Accessed May 5,
2017.
http://www.reuters.com/article/us-global-fx-peaktradingidUSKCN0VK1UD
Nison, Steve. 2001. Japanese Candlestick Charting Techniques (Second
Edition). New Jersey: Prentice Hall Press.
NYSE (New York Stock Exchange). 2017. “Daily NYSE Group Volume
in NYSE Listed, 2017.” Accessed May 5, 2017.
http://www.nyxdata.com/nysedata/asp/factbook/viewer_edition.asp?m
ode=table&key=3141&category=3
O'Shea, Arielle, and James Royal. 2018. “Best Forex Brokers for 2018.”
Accessed July 3, 2018.
https://www.nerdwallet.com/blog/investing/best-forex-brokers/
Parado, Robert. 2011. The Evaluation and Optimization of Trading
Strategies. Hoboken, New Jersey: John Wiley & Sons, Inc.
Peters, Edgar E. 1994. Fractal Market Analysis: Applying Chaos Theory
to Investment and Economics. New Jersey, United States: John Wiley
& Sons.
122
References
Perron, Pierre. 1997. “Further Evidence on Breaking Trend Functions in
Macroeconomic Variables.” Journal of Econometrics 80 (2): 355-385.
Reilly, Frank, and Keith C. Brown. 2011. Investment Analysis and
Portfolio Management. Massachusetts: Cengage Learning.
Reklaitis, Victor. 2017. “United’s stock falls 1.1%, wipes out $255 million
off the airline’s market cap.” Market Watch, April 12. Accessed April
15, 2017. http://www.marketwatch.com/story/uniteds-stock-is-set-tofall-5-and-wipe-1-billion-off-the-airlines-market-cap-2017-04-11
Reinbold, Brian, and Yi Wen. 2018. “Understanding the Trade Imbalance
and Employment Decline in U.S. Manufacturing.” Economic Synopses
15: 1-3.
Roache, Shaun K., and Marco Rossi. 2010. “The Effects of Economic
News on Commodity Prices.” The Quarterly Review of Economics and
Finance 50(3): 377-385.
Sure Trader. 2016. “Margin Fees.” Accessed April 3, 2016.
https://suretrader.com/trading-fees/margin-fees/
Stock Charts. 2016. “Introduction to Candlesticks.” 2016. Accessed April
6, 2016.
http://stockcharts.com/school/doku.php?id=chart_school:chart_analysi
s:introduction_to_candlesticks
Stock Charts. 2016a. “Technical Analysis 101 - Part 11.” 2016. Accessed
April 7, 2016.
http://stockcharts.com/school/doku.php?id=chart_school:overview:tech
nical_analysis_b
—. 2016b. “Technical Analysis 101 - Part 12.” 2016. Accessed April 7,
2016.
http://stockcharts.com/school/doku.php?id=chart_school:overview:tech
nical_analysis_c
Trade Station. 2016. “Account & Margin Requirements.” 2016. Accessed
April 3, 2016. https://www.tradestation.com/products/stocks-and-etfs/
account-and-margin-requirements#
US BLS (United States Bureau of Labor Statistics). 2018. “Unemployment
rate - Seasonally Adjusted.” Accessed July 6, 2018.
https://www.google.com/publicdata/explore?ds=z1ebjpgk2654c1_&me
t_y=unemployment_rate&hl=en&dl=en
US SEC (United States Securities and Exchange Commission). 2016.
“Short Sale Restrictions.” US SEC. Accessed October 15, 2016.
https://www.sec.gov/answers/shortrestrict.htm
Wagner, Wayne H., and Sheila C. Lau. 1971. “The Effect of
Diversification on Risk.” Financial Analysts Journal 27 (6): 48-53.
A Practical Introduction to Day Trading
123
Wilder, J. Welles. 1978. New Concepts in Technical Trading Systems.
Trend Research.
Yahoo Finance. 2016a. “Finance Home.” Yahoo Finance. Accessed July
25, 2016. https://finance.yahoo.com/
—.2016b. “TROVW TrovaGene, Inc.” Yahoo Finance. Accessed July 12,
2016.
http://finance.yahoo.com/quote/TROVW/history?period1=1451620800
&period2=1468296000&interval=1d&filter=history&frequency=1d
Zivot Eric, and D. W. Andrews. 1992. “Further Evidence on the Great
Crash, the Oil-Price Shock, and the Unit-Root.” Journal of Business &
Economic Statistics 10 (0): 251-270.