The Handbook of Technical Analysis The Wiley Trading series features books by traders who have survived the market’s ever changing temperament and have prospered—some by reinventing systems, others by getting back to basics Whether a novice trader, professional or somewhere in-between, these books will provide the advice and strategies needed to prosper today and well into the future For more on this series, visit our Web site at www.WileyTrading.com Founded in 1807, John Wiley & Sons is the oldest independent publishing company in the United States With offices in North America, Europe, Australia and Asia, Wiley is globally committed to developing and marketing print and electronic products and services for our customers’ professional and personal knowledge and understanding The Handbook of Technical Analysis The Practitioner’s Comprehensive Guide to Technical Analysis Mark Andrew Lim Cover Design: Wiley Cover Image: ©Krystian Nawrocki / iStockphoto.com Copyright © 2016 by John Wiley & Sons Singapore Pte Ltd Published by John Wiley & Sons Singapore Pte Ltd Fusionopolis Walk, #07-01, Solaris South Tower, Singapore 138628 All rights reserved No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as expressly permitted by law, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center Requests for permission should be addressed to the Publisher, John Wiley & Sons Singapore Pte Ltd., Fusionopolis Walk, #07-01, Solaris South Tower, Singapore 138628, tel: 65-6643-8000, fax: 65-6643-8008, e-mail: enquiry@wiley.com Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose No warranty may be created or extended by sales representatives or written sales materials The advice and strategies contained herein may not be suitable for your situation You should consult with a professional where appropriate Neither the publisher nor the author shall be liable for any damages arising herefrom Other Wiley Editorial Offices John Wiley & Sons, 111 River Street, Hoboken, NJ 07030, USA John Wiley & Sons, The Atrium, Southern Gate, Chichester, West Sussex, P019 8SQ, United Kingdom John Wiley & Sons (Canada) Ltd., 5353 Dundas Street West, Suite 400, Toronto, Ontario, M9B 6HB, Canada John Wiley & Sons Australia Ltd., 42 McDougall Street, Milton, Queensland 4064, Australia Wiley-VCH, Boschstrasse 12, D-69469 Weinheim, Germany ISBN 978-1-118-49891-0 (Paperback) ISBN 978-1-118-49893-4 (ePDF) ISBN 978-1-118-49892-7 (ePub) Typeset in 11/14 pt Sabon LT Std Roman by Aptara Inc., New Delhi, India Printed in Singapore by Markono Print Media Pte Ltd 10 I dedicate this work to my family, for their unconditional support and encouragement through thick and thin Contents Foreword xiii Preface xv Acknowledgments xxi About the Author xxiii Chapter Introduction to the Art and Science of Technical Analysis 1.1 Main Objective of Technical Analysis 1.2 Dual Function of Technical Analysis 1.3 Forecasting Price and Market Action 1.4 Classifying Technical Analysis 1.5 Subjectivity in Technical Analysis 1.6 Basic Assumptions of Technical Analysis 1.7 Four Basic Assumptions in the Application of Technical Analysis 1.8 Market Participants 1.9 Chapter Summary Chapter Review Questions 1 3 11 16 30 39 40 42 43 CHAPTER Introduction to Dow Theory 45 CHAPTER Mechanics and Dynamics of Charting 65 CHAPTER Market Phase Analysis 99 2.1 Origins and Proponents of Dow Theory 2.2 Basic Assumptions of Dow Theory 2.3 Challenges to Dow Theory 2.4 Chapter Summary Chapter Review Questions 3.1 The Mechanics and Dynamics of Charting 3.2 Gap Action: Four Types of Gaps 3.3 Constant Chart Measures 3.4 Futures Contracts 3.5 Chapter Summary Chapter Review Questions 4.1 Dow Theory of Market Phase 4.2 Chart Pattern Interpretation of Market Phase 4.3 Volume and Open Interest Interpretation of Market Phase 4.4 Moving Average Interpretation of Market Phase 4.5 Divergence and Momentum Interpretation of Market Phase 4.6 Sentiment Interpretation of Market Phase 4.7 Sakata’s Interpretation of Market Phase 4.8 Elliott’s Interpretation of Market Phase 4.9 Cycle Analysis Interpretation of Market Phase 45 46 62 64 64 65 72 73 89 97 98 99 104 112 115 116 118 119 120 122 vii Contents 4.10 Chapter Summary Chapter Review Questions 124 124 CHAPTER Trend Analysis 125 5.1 Definitions of a Trend 5.2 Quality of Trend: 16 Price Characteristics Impacting Future Price Action and Trend Strength 5.3 Price and Trend Filters 5.4 Trend Participation 5.5 Price Inflection Points 5.6 Trendlines, Channels, and Fan Lines 5.7 Trend Retracements 5.8 Gaps and Trends 5.9 Trend Directionality 5.10 Drummond Geometry 5.11 Forecasting Trend Reversals 5.12 Chapter Summary Chapter Review Questions 125 132 144 145 148 155 166 166 168 169 170 171 171 CHAPTER Volume and Open Interest 173 CHAPTER Bar Chart Analysis 209 CHAPTER Window Oscillators and Overlay Indicators 235 CHAPTER Divergence Analysis 267 6.1 The Mechanics of Volume Action 6.2 Volume Oscillators 6.3 Chapter Summary Chapter Review Questions 7.1 Price Bar Pattern Characteristics 7.2 Price Bar Pattern Characteristics 7.3 Popular Bar Reversal Patterns 7.4 Volatility‐Based Breakout Patterns 7.5 Chapter Summary Chapter Review Questions 8.1 Defining Indicators and Oscillators 8.2 Eight Ways to Analyze an Oscillator 8.3 Cycle Period, Multiple Timeframes, and Lagging Indicators 8.4 Input Data 8.5 Trend Trading Using Oscillators 8.6 Window Oscillators 8.7 Overlay Indicators 8.8 Chapter Summary Chapter Review Questions 9.1 Definition of Divergence 9.2 General Concept of Divergence 9.3 Standard and Reverse Divergence 9.4 Price Confirmation in Divergence Analysis 9.5 Signal Alternation between Standard and Reverse Divergence 9.6 More Examples of Divergence 9.7 Chapter Summary Chapter Review Questions viii 173 203 208 208 209 211 218 230 233 233 235 240 252 253 255 255 262 266 266 268 272 291 323 337 338 354 355 the Handbook of Technical Analysis Short at a high price and cover at a lower price Short at a relatively low price and cover at an even lower price Listed below are the some of the strengths of each approach with respect to timing the markets Technically Based Market Timing offers the ability to ■■ Provide precise entry and exit prices ■■ Provide the precise time of entry and exit ■■ Provide real‐time bullish and bearish signals ■■ Provide real‐time entry and exit price triggers ■■ Scale in and out based on significant price levels ■■ Time entries and exits based on volatility behavior of the underlying ■■ Exit extended trends at technically significant price‐reversal levels ■■ Time entries and exits based on market order flow ■■ Define percent risk in terms of significant price levels ■■ Use volume and open interest analysis to gauge strength of an underlying move in order to time entries and exits ■■ Use market breadth and broad market sentiment to gauge the strength of an underlying move in order to time entries and exits ■■ Forecast potential peaks (for shorting or liquidating positions) as well as potential troughs (for getting long and covering positions) via the use of cycle and seasonality analysis Fundamentally Based Market Timing offers the ability to: ■■ Gauge undervalued stocks with a potential to appreciate in value, but lacking information regarding the precise price or time to get long or to cover ■■ Gauge overvalued stocks with a risk of depreciating in value, but lacking information regarding the precise price or time to get short or to liquidate ■■ Screen and participate in fundamentally strong stocks in a sector or industry as part of an active asset allocation or rotation strategy, but lacking information regarding the precise price or time to get long The Fundamentalist versus Technical Analysts Listed below are some characteristics of the fundamentalist and technical analyst: The Fundamentalist: ■■ Is mainly concerned with intrinsic value ■■ Strives to understand the underlying causes for potential market moves ■■ Is focused on which company to participate in ■■ Can tell you which company to invest in, but cannot tell you the most advantageous moment to start participating in that stock The Technical Analyst: ■■ Is mainly concerned with structure and dynamics of market and price action ■■ Is more concerned with the effects of potential market moves rather than the cause of them 10 Introduction to the Art and Science of Technical Analysis Cannot usually determine what the intrinsic value of an asset is or whether it is under-or overvalued, but is able to determine precisely when to start participating, purely from the perspective of price performance ■■ Is not concerned with the underlying factors that led to the rise in price; this is irrelevant for all practical purposes as they believe that price is a reflection of all information available in the markets and therefore that is all that really matters ■■ In short, from what we have covered so far, we know that technical analysis: Uses past information ■■ Uses charts ■■ Identifies past and current price action ■■ Forecasts potential future price action based on historical price behavior (especially the start of a new trend) ■■ Technical Data and Information Technical analysts study market action Market action itself is mainly comprised of the study of: Price action ■■ Volume action ■■ Open interest action ■■ Sentiment ■■ Market breadth ■■ Flow of funds ■■ Of all the data that technical analysts employ, price is the most important, followed closely by volume action Price itself is comprised of an opening, high, low, and closing price, normally referred to as OHLC data OHLC data normally refers to the daily opening, high, low, and closing prices, but it may be used to denote the OHLC of any bar interval, from 1‐minute bars right up to the monthly and yearly bars 1.4 Classifying Technical Analysis Technical analysis may be categorized into four distinct branches, that is, classical, statistical, sentiment, and behavioral analysis Regardless of which branch is employed, all analysis is eventually interpreted via the various behavioral traits, filters, and biases unique to each analyst Behavioral traits include both the psychological and emotional elements See Figure 1.6 Classical technical analysis involves the use of the conventional bar, chart, and Japanese candlestick patterns, oscillator and overlay indicators, as well as market breadth, relative strength, and cycle analysis Statistical analysis is more quantitative, as opposed to the more qualitative nature of classical technical analysis It 11 the Handbook of Technical Analysis Figure 1.6 The Four Branches of Technical Analysis studies the dispersion, central tendencies, skewness, volatility, regression analysis, hypothesis testing, correlation, covariance, and so on Sentiment analysis is concerned with the psychology of market participants, which includes their emotions and level of optimism or pessimism in the markets It studies professional and public opinion via polls and questionnaires, trading and investment decisions via flow of funds in the markets, as well as the positions taken by large institutions and hedgers Finally, behavioral analysis studies the way market participants react to news, profit and losses, the actions of other market participants, and with their own psychological and emotional biases, preferences, and expectations Mean Reverting versus Non–Mean Reverting Approach The type of technical studies employed also depends on the approach taken by traders and analysts with respect to their personal preferences and biases regarding the action of price in the markets Basically, traders either adopt a contrarian or a momentum‐seeking type approach Being more contrarian in their approach implies that they not usually expect the price to traverse large distances In fact they are constantly on the lookout for impending reversals in the markets In essence, they expect price to be more mean reverting, returning to an average price or balance between supply and demand Those that adopt the mean‐reverting approach prefer to employ technical studies that help pinpoint levels of overbought and oversold activity, which includes divergence analysis, regression analysis, moving average bands, and Bollinger bands They prefer to trade consolidations rather than trend action They normally buy at support and short at resistance Limit entry orders are their preferred mode of order entry Conversely, being more momentum seeking in their approach implies that they usually expect the price to traverse large distances and for trends to continue to remain intact They are constantly on the lookout for continuation type breakouts in the markets In short, 12 Introduction to the Art and Science of Technical Analysis Figure 1.7 Mean Reverting versus Non–Mean Reverting Approaches they expect price to be more non–mean reverting, where demand creates further demand and supply creates further supply, both driven by a powerful positive‐ feedback cycle Those that adopt the non–mean reverting approach prefer to employ technical studies that help pinpoint breakout or trend continuation activity, which includes chart pattern breakouts, moving average breakouts, Darvas Box breakouts, and Donchian channel breakouts They prefer to trade trends rather than ranging action They normally short at the breach of support and long at breach of resistance Stop entry orders are their preferred mode of entry into the markets See Figure 1.7 Advantages and Disadvantages of Technical Analysis The advantages of applying technical analysis to the markets are: It is applicable across all markets, instruments, and timeframes, where price patterns, oscillators, and overlay indicators are all treated in exactly the same manner No new learning is required in order to trade new markets or timeframes, unlike in fundamental analysis where the analyst must be conversant with the specifics of each stock or market ■■ There is no need to study the fundamentals of the markets traded or analyzed in order to apply technical analysis, since technical analysts believe that all information that impacts or potentially may impact the stock or market is already reflected in the price on the charts ■■ Technical analysis provides a clear visual representation of the behavior of the markets, unlike in fundamental analysis where most of the data is in numerical form ■■ 13 the Handbook of Technical Analysis It provides timely and precise entry and exit price levels, preceded by technical signals indicating potential bullishness or bearishness It has the ability to also pinpoint potential time of entry via time projection techniques not available to fundamentalists Fundamental analysis does not provide the exact price or time of entry ■■ It makes the gauging of market risk much easier to visualize Volatility is more obvious on the charts than it is in numerical form ■■ The concerted effort of market participants acting on significantly clear and obvious price triggers in the markets helps create the reaction required for a more reliable trade This is the consequence of the self‐fulfilling prophecy ■■ The disadvantages of applying technical analysis are: It is subjective in its interpretation A certain price pattern may be perceived in numerous ways Since every bullish interpretation has an equal and opposite bearish interpretation, all analysis is susceptible to the possibility of interpretational ambiguity Unfortunately, all manners of interpretation, regardless of the underlying analysis employed—be it fundamental, statistical, or behavioral—are equally subjective in content and form ■■ A basic assumption of technical analysis is that price behavior tends to repeat, making it possible to forecast potential future price action Unfortunately this tendency to repeat may be disrupted by unexpected volatility in the markets caused by geopolitical, economic, or other factors Popular price patterns may also be distorted by new forms of trade execution that may impact market action, like automated, algorithmic, or high‐frequency program trading where trades are initiated in the markets based on non‐classical patterns This interferes with the repeatability of classic chart patterns ■■ Charts provide a historical record of price action It takes practice and experience to be able to identify classical patterns in price Though this skill can be mastered with enough practice, the art of inferring or forecasting future price action based on past prices is much more difficult to master The practitioner needs to be intimately familiar with the behavior of price at various timeframes and in different markets Although classical patterns may be applied equally across all markets and timeframes equally, there is still an element of uniqueness associated with each market action and timeframe ■■ It is argued that all market action is essentially a random walk process, and as such applying technical analysis is pointless as all chart patterns arise out of pure chance and are of no significance in the markets One must remember that if this is the case, then all forms of analysis are ineffective, whether fundamental, statistical, or behavioral Since the market is primarily driven by perception, we know that the random‐walk process is not a true representation of market action, since market participants react in very specific and predictable ways Though there is always some element of randomness in the markets caused by the uncoordinated actions of a large number of market ■■ 14 Introduction to the Art and Science of Technical Analysis participants, one can always observe the uncanny accuracy with which price tests and reacts at a psychologically significant barriers or prices It is hard to believe that price action is the result of random acts of buying and selling by market participants where the participants are totally unencumbered by cost, biases, psychology, or emotion ■■ The strong form of the Efficient Market Hypothesis (EMH) argues that since the markets discount all information, price would have already adjusted to the new information and any attempt to profit from such information would be futile This would render the technical analysis of price action pointless, with the only form of market participation being passive investment But such efficiency would require that all market participants react instantaneously to all new information in a rational manner This in itself presents an insurmountable challenge to EMH The truth is that no system comprising disparate parts in physical reality reacts instantaneously with perfect coordination Hence it is fairly safe to assume that although absolute market efficiency is not attainable, the market does continually adjust to new information, but at a much lower and less‐efficient rate of data discounting Therefore, technical analysis remains a valid form of market investigation until the markets attain a state of absolute and perfect efficiency ■■ Another argument against technical analysis is the idea of the Self‐Fulfilling Prophecy (SFP) Proponents of the concept contend that prices react to technical signals not because the signals themselves are important or significant, but rather because of the concerted effort of market participants acting on those signals that make it work This may in fact be advantageous to the market participants The trick is in knowing which technical signals would be supported by a large concerted action The logical answer would be to select only the most significantly clear and obvious technical signals and triggers Of course, one can further argue that such signals, if they appear to be reliable indicators of support and resistance, would begin to attract an increasing number of traders as time passes This would eventually lead to traders vying with each other for the best and most cost‐effective fills What seems initially like the concerted action of all market participants now turns into competition with each other Getting late fills would be costly as well as reduce or wipe out any potential for profit This naturally results in traders attempting to preempt each other for the best fills Traders start vying for progressively earlier entries as price approaches the targeted entry levels, leading finally to entries that are too distant from the original entry levels, increasing risk and reducing any potential profits This disruptive feedback cycle eventually erodes the reliability of the signals, as price fails to react at the expected technical levels Price finally begins to react reliably again at the expected technical levels as traders stop preempting each other and abandon or disregard the strategy that produced the signals The process repeats Therefore, SFP may result in technical signals evolving in a kind of six‐stage duty cycle, where the effects of SFP may be advantageous and desirable to traders in the early stages but eventually result in forcing traders into untenable positions See Figure 1.8 15 the Handbook of Technical Analysis Figure 1.8 The Idealized Six‐Stage Self‐Fulfilling Prophecy Cycle 1.5 Subjectivity in Technical Analysis As with most forms of analysis, technical analysis has both objective and subjective aspects associated with its application It is objective insofar as the charts represent a historical record of price and market action But it is subjective when the technical analyst attempts to analyze the data Analyzing price and market action consists of three main activities, namely: Identifying price and indicator patterns Interpreting the data Inferring potential future price behavior Analyzing price and market action is ultimately subjective because all analysis is interpreted through various behavioral traits, filters, and biases unique to each analyst or observer Behavioral traits include both the psychological and emotional elements As a consequence, each analyst will possess a slightly different perception of the market and its possible future behavior Subjectivity in the Choice of Analysis and Technical Studies The sheer number of ways to analyze an individual chart contributes to the overall level of subjectivity associated with each forecast The problem is twofold: What is the most appropriate form of technical analysis that should be applied to a particular chart? ■■ What is the most appropriate choice of indicators to apply to a particular chart? ■■ 16 Introduction to the Art and Science of Technical Analysis Figure 1.9 A Simple Price Chart Source: MetaTrader These are the usual questions that plague novices The following charts depict the various popular forms of analysis that can be applied to a basic chart of price action The following examples are by no means exhaustive Figure 1.9 starts off with a plain chart devoid of any form of analysis The next chart, Figure 1.10, shows the application of basic trendline analysis on the same chart, tracking the flow of price action in the market Figure 1.10 Trendline Analysis on the Same Chart Source: MetaTrader 17 the Handbook of Technical Analysis Figure 1.11 Moving Average Analysis on the Same Chart Source: MetaTrader In Figure 1.11, moving average analysis is now employed to track the same flow of price action and to provide potential points of entry as the market rises and falls Figure 1.12 depicts the application of chart pattern analysis to track and forecast the shorter‐term bullish and bearish movements in price Figure 1.13 is an example of applying two forms of technical analysis, that is, linear regression analysis and divergence analysis to track and forecast potential market tops and bottoms Notice that the market top coincided perfectly with the upper band of the linear regression line, with an early bearish signal seen in the form of standard bearish divergence on the commodity channel index (CCI) indicator Figure 1.12 Chart Pattern Analysis on the Same Chart Source: MetaTrader 18 Introduction to the Art and Science of Technical Analysis Figure 1.13 Linear Regression and Divergence Analysis on the Same Chart Source: MetaTrader Figure 1.14 is an example of applying a couple of additional forms of analysis to the basic linear regression band In this chart, price action analysis is used in conjunction with volume analysis to forecast a potential top in the market, evidenced by the preceding parabolic move in price that is coupled by a blow‐off In Figure 1.15, volatility band, volume, and overextension analysis are all employed to seek out potential reversals in the market We observe that price exceeds the upper volatility band, which may potentially be an early indication of price exhaustion, especially since it is accompanied by a significant volume spike The moving average convergence‐divergence (MACD) indicator is also seen to be residing at historically overbought levels, which is another potentially bearish indication Figure 1.14 Linear Regression and Volume Analysis on the Same Chart Source: MetaTrader 19 the Handbook of Technical Analysis Figure 1.15 Volatility Band, Volume, and Overextension Analysis on the Same Chart Source: MetaTrader As we can see from just a few forms of analysis presented in the preceding charts, there are many ways to view the action of the markets, depending on the context of the analysis employed For example, if the analyst is more interested in viewing and understanding the action of price within the context of over‐reaction or price exhaustion in the markets, he or she may opt to apply technical studies that track levels or areas of potential over‐reaction or price exhaustion Technical studies that tract such behavior include linear regression bands, Bollinger bands, moving average percentage bands, Keltner and Starc bands, areas of prior support and resistance, and so on Alternatively, if the analyst is more interested in viewing and understanding the action of price within the context of market momentum, he or she may instead opt to apply breakout analysis of chart patterns, trendlines, moving averages, and so on As long as the reason for using a particular form of analysis is clear, there should be no confusion as to what the studies are indicating Contradictory, Confirmatory, and Complementary Signals There are many instances when two oscillator signals are in clear and direct opposition with each other This is inevitable, as each oscillator is constructed differently The mathematics underlying each oscillator varies with the purpose it is designed for, and in most cases, it involves the manipulation of price, volume, and open interest data A few reasons for conflicting oscillator and indicator signals are: The mathematical construction of each oscillator or indicator is different Each oscillator or indicator tracks a different time horizon ■■ Two identical oscillators may issue inconsistent readings due to missing data on one of the charting platforms ■■ Two identical oscillators may also issue inconsistent readings due to variations in the accuracy, quality, and type of data available on different charting platforms ■■ ■■ 20 Introduction to the Art and Science of Technical Analysis For example, applying an oscillator that uses price, volume, and open interest as part of its calculation will yield inconsistent readings should one of the data be unavailable on the charting platform The analysts may not be aware of the missing data and struggle to make sense of the inconsistency The accuracy of the data is also of paramount importance for effective analysis of price and market action Dropouts in the data as well as the inclusion or exclusion of non‐trading days will cause inconsistent readings between charting platforms There may also be variations in the oscillator readings should volume be replaced with tick volume, sometime also referred to as transaction volume Tick volume tracks the number of transactions over a specified time interval, irrespective of the size of the transactions It is also important to note that conflicting signals may not always be in fact conflicting As pointed out, the time horizons over which each signal is applied may be different In Figure 1.16 we observe that the CCI readings over the range of prices are markedly different The 20‐period CCI indicates a slightly overbought market whereas the 100‐period CCI suggests that prices are slightly oversold There is in fact no real conflict between the two apparently opposing signals The indicators are merely pointing out that prices are slightly overbought or overextended in the short term, but over the longer term, prices are in fact slightly oversold, that is, relatively cheap Therefore, instead of viewing the signals as opposing or contradictory, the astute trader immediately realizes that the most advantageous point for initiating a long entry would be when prices are cheap both in the long and short term This is easily identified on the charts by looking for oversold readings on both the 20‐ and Figure 1.16 Conflicting Signals on the Daily Alcoa Inc Chart Courtesy of Stockcharts.com 21 the Handbook of Technical Analysis 100‐period CCI within the area of consolidation, as indicated at Point Therefore, the trader may decide to go long once price penetrates the high of the candlestick indicated on the chart In this example, we see conflicting signals actually complementing each other and affording the trader an advantageous entry at relatively low prices The important point to remember is that any form of analysis may be employed, as long as the analyst is intimately familiar with the peculiarities associated with each form of analysis It is better to be conversant with one form of analysis than to employ a slew of technical approaches without fully grasping the intricacies of each approach This leads to confusion and ineffective analysis It must be noted that combining technical studies will frequently result in both confirmatory and contradictory signals as we have seen, with many of the signals being also complementary as well Only add studies once the first form of analysis is fully mastered The practitioner must always remember that no form of analysis is always perfectly representative of the market, and it is inevitable that different forms of analysis will many times lead to conflicting signals Subjectivity in Pattern Identification As mentioned, interpretation and inference of potential future price action based on historical price behavior is essentially an exercise in subjectivity Each analyst will interpret and infer future price action according to his or her own experience, knowledge, objectives, beliefs, expectations, predilections, emotional makeup, psychological biases, and interests The identification of price patterns may also present some challenge to the novice practitioner Occasionally, the markets will conveniently trace out various price patterns that may cause some confusion Refer to Figure 1.17 Figure 1.17 Conflicting Chart Pattern Signals 22 Introduction to the Art and Science of Technical Analysis In this example, we see two chart patterns indicating potentially contradictory signals The ascending triangle is regarded as a bullish indication, while the complex head and shoulders formation is potentially bearish Therefore, as price starts to contract, forming a symmetrical triangle, an analyst may be somewhat perplexed at the conflicting signals, being unable to provide or issue a clear forecast as to whether the market is indeed potentially bullish or bearish One way to resolve this apparent conflict is to first identify the size of each pattern The sentiment associated with larger patterns or formations will take precedence over that of smaller formations These larger formations are more representative of the longer‐term sentiment whereas the smaller formations are more indicative of short‐term sentiment Hence in our example, the bullish sentiment associated with the ascending triangle takes precedence over the bearish sentiment associated with the complex head and shoulders formation Therefore, until price breaches the complex head and shoulders neckline, the entire formation may be regarded as a potentially bullish pattern Following this simple rule helps reduce some of the subjectivity involved in reading price and chart formations Figure 1.18 depicts an idealized scenario where all the chart formations are potentially bearish There is no conflict in sentiment between these formations as they are all in perfect agreement The smaller formations act as additional evidence and add to the overall bearish sentiment There is also a lesser amount of subjectivity involved when reading the sentiment associated with formations that are in perfect agreement Nevertheless, it should be noted that although such formations may appear somewhat more straightforward with respect to Figure 1.18 Chart Pattern with Complementary Signals 23 the Handbook of Technical Analysis inferring potential future price direction, any upside breakout of the larger descending triangle may well precipitate a vigorous and rapid rally in prices due to the unexpected nature of such a move Traders must exercise caution especially when shorting such a formation as prices can quickly explode to the upside, caused by an avalanche of short covering Interpretational and Inferential Subjectivity This element of subjectivity with respect to interpretation and inference is not merely confined to applications in technical analysis In fact, every form of analysis involves a certain amount of subjectivity and arbitrariness when it comes to its interpretation For example, let us assume that the price of oil has risen significantly This event in itself can be interpreted in two different ways One fundamentalist may strongly believe that this rise in oil prices will impact the markets adversely as it will raise the underlying cost of commodities, whereas another fundamentalist may strongly believe that the rise in oil prices is a direct result of market demand, a bullish scenario indicating a healthy and growing economy In another example, a technical analyst may strongly believe that an overbought oscillator reading is a clear indication that the trend is strong with further continuation expected in price, whereas another technical analyst may strongly believe that the overbought signal is a clear indication that the market may be already overextended and therefore expects a reversal in trend The beginner quickly realizes, after some reflection, that for every bullish interpretation, there exists an equal and opposite bearish interpretation This is one of the main reasons why forecasting is regarded as largely subjective Subjectivity and Selective Perception Human bias is another factor that adds to the degree of subjectivity when attempting to interpret technical signals Chartists will many times ignore signals that conflict with their preconceived ideas of where the markets ought to be at any one time They only select oscillators and indicator signals that support their analysis of the market For example, a chartist uses three oscillators, the MACD, relative strength index (RSI), and stochastics The chartist has a bullish view of the markets and believes that it is about to break to the upside All of the oscillators have bullish readings except for stochastics The chartist ignores the stochastics signal because it does not agree with his or her view of the markets On a subsequent occasion, it is MACD that is not in agreement with the chartist’s view, and only the signals from the other two oscillators are heeded This is known as selective perception See Figure 1.19 Selective perception adds to the subjectivity of the forecast, as there is no fixed point of reference or basis for making decisions based on evidence Choosing only signals that agree with one’s view will lead to biased and erroneous interpretations and unfounded forecasts In fact, it is when there are discrepancies in the signals that the chartist gains the most information from the markets, as it may be an indication that there could well be some form of underlying weakness in the markets 24 ... 98 99 10 4 11 2 11 5 11 6 11 8 11 9 12 0 12 2 vii Contents 4 .10 Chapter Summary Chapter Review Questions 12 4 12 4 CHAPTER Trend Analysis 12 5 5 .1 Definitions of a Trend 5.2 Quality of Trend: 16 Price... Australia Wiley-VCH, Boschstrasse 12 , D-69469 Weinheim, Germany ISBN 978 -1- 118 -498 91- 0 (Paperback) ISBN 978 -1- 118 -49893-4 (ePDF) ISBN 978 -1- 118 -49892-7 (ePub) Typeset in 11 /14 pt Sabon LT Std Roman by... 5 .10 Drummond Geometry 5 .11 Forecasting Trend Reversals 5 .12 Chapter Summary Chapter Review Questions 12 5 13 2 14 4 14 5 14 8 15 5 16 6 16 6 16 8 16 9 17 0 17 1 17 1 CHAPTER Volume and Open Interest 17 3