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Value in time

  1. 1. fm JWBK129-Willain March 18, 2008 14:0 Char Count= 0 vi
  2. 2. fm JWBK129-Willain March 18, 2008 14:0 Char Count= 0 Value in Time i
  3. 3. fm JWBK129-Willain March 18, 2008 14:0 Char Count= 0 Founded in 1807, John Wiley & Sons is the oldest independent publishing company in the United States. With offices in North America, Europe, Aus- tralia, 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 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 a list of available titles, please visit our Web site at www.Wiley ii
  4. 4. fm JWBK129-Willain April 19, 2008 11:54 Char Count= 0 Value in Time Better Trading through Effective Volume PASCAL WILLAIN John Wiley & Sons, Inc. iii
  5. 5. fm JWBK129-Willain March 18, 2008 14:0 Char Count= 0 Copyright C 2008 by Pascal Willain. All rights reserved. Published by John Wiley & Sons, Inc., Hoboken, New Jersey. Published simultaneously in Canada. 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 permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) 750-8400, fax (978) 646-8600, or on the web at Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748-6011, fax (201) 748-6008, or online at 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 author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. For general information on our other products and services or for technical support, please contact our Customer Care Department within the United States at (800) 762-2974, outside the United States at (317) 572-3993 or fax (317) 572-4002. Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic books. For more information about Wiley products, visit our web site at Library of Congress Cataloging-in-Publication Data: Willain, Pascal, 1959– Value in time : better trading through effective volume / Pascal Willain. p. cm. – (Wiley trading series) Includes bibliographical references and index. ISBN 978-0-470-11873-3 (cloth) 1. Investment analysis. 2. Stocks–Charts, diagrams, etc. I. Title. HG4529.W539 2008 332.63 2042–dc22 2007049358 Printed in the United States of America. 10 9 8 7 6 5 4 3 2 1 iv
  6. 6. fm JWBK129-Willain March 18, 2008 14:0 Char Count= 0 The world’s ever-growing population increasingly affects our daily lives. Like never before, this demographic challenge is forcing us to address critical issues: boosting the production of basic foods, finding new sources of energy, recycling base metals, and tackling environmental issues, to name a few. In my view, the stock market provides people with a simple way to take part in these high-growth sectors by investing in companies that offer solutions to these problems. However, because many people are too busy just trying to survive, they will not be able to adapt to or even recognize the coming changes. Simply dedicating this book to these people does not help much, but perhaps monetary donations will. I have decided to offer free of charge the Effective Volume tool described in Chapter 1. I welcome, however, donations to the Nello and Patrasche Foundation, a foundation that my wife and I created some years ago for the benefit of handicapped orphans. v
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  8. 8. fm JWBK129-Willain March 18, 2008 14:0 Char Count= 0 Contents Foreword xi Acknowledgments xiii Introduction: Revolution Is at Your Doorstep 1 PART ONE The Set of Tools That Will Change Technical Analysis 9 CHAPTER 1 Effective Volume: An Open Window into the Market 11 Traders Get a Secret New Tool: A Brief Introduction to the Trading Mechanisms and the Market Players 14 Volume That Moves the Markets 20 Effective Volume 30 Practical Examples of Effective Volume Calculations 40 Technical Section: How to Calculate the Separation Volume 51 Improve Your Trading: Decide on the Big Picture 57 A Comparison with Traditional Tools 59 What We Learned Regarding Effective Volume 66 CHAPTER 2 Price and Value: The Active Boundaries Indicator 67 Buy Low 67 Traditional Measure of “Cheap" 69 Why Do Trends Exist? 81 Grandmothers Are Always Right! 101 vii
  9. 9. fm JWBK129-Willain March 18, 2008 14:0 Char Count= 0 viii CONTENTS For Math Lovers: How to Calculate the Active Boundaries 109 What We Learned Regarding Active Boundaries 110 CHAPTER 3 When Volume Diverges from Price 113 Effective Volume: Two Arrows from One Bow 114 Price and Effective Volume Trends 118 Price-Volume Divergence Analysis 134 Examples of Divergence Analysis 144 How to Set the Optimal Analysis Window 176 Empty Trading Minutes 181 What We Learned Regarding Divergence Analysis 183 CHAPTER 4 Supply and Demand: The Key to Trading 185 Supply/Demand Equilibrium 186 Funds’ Strategies 205 Funds and Market Manipulation 211 What We Learned Regarding the Supply Analysis 218 PART TWO Trading Strategies 219 CHAPTER 5 Performance: The Risk/Return Balance 221 The Trading Strategy 223 Optimizing Profits 226 Minimizing Risks 245 Measures of Risk-Adjusted Performance: The Sharpe and Burke Ratios 260 What We Learned in This Chapter 262 CHAPTER 6 Automated Trading Systems 265 Production of Trading Signals 268 Trading Strategies 274 What We Learned in This Chapter 317
  10. 10. fm JWBK129-Willain March 18, 2008 14:0 Char Count= 0 Contents ix PART THREE The Bonus Section 319 CHAPTER 7 The Market Is a Two-Way Street: Shorting Strategies 321 The Short Sale “Tick Test” Rule 321 How to Use This Book’s Tools for Short Trading 322 What We Learned in This Chapter 340 CHAPTER 8 Market and Sector Analysis 341 When Is the Market Becoming Expensive? 342 Sector Analysis 350 What We Learned in This Chapter 361 Conclusion 363 Data Providers 371 Sources 373 About the Author 375 Index 377
  11. 11. fm JWBK129-Willain March 18, 2008 14:0 Char Count= 0 x
  12. 12. fm JWBK129-Willain March 18, 2008 14:0 Char Count= 0 Foreword ou have opened a revolutionary book that explodes the envelope of Y standard technical analysis. It introduces several new tools that can help you recognize when a trend is likely to reverse. It reveals new ways to profit from trends and their reversals. Pascal Willain used inexpensive off-the-shelf software to slice each trading day of a stock into one-minute segments, like cutting a long stick of salami into thin slices. He measures each slice to see whether prices rise or fall during that minute and discards the minutes with no changes. He finds the average one-minute volume for the day and separates the minutes with price changes into those with above-average or below-average volume. In each group, he adds up the volume of minutes with rising prices and sub- tracts the volume of minutes with falling prices. This gives him two cumu- lative volume lines: one for the minutes with above-average volume and the other minutes with for below-average volume. He named them Large and Small Effective Volume. Pascal explains that the minutes with above-average volume reflect the impact of the big money. He discovered that Large Effective Volume often has predictive value. When you find a condition in which the big money starts pushing up a stock while the small money remains negative or neu- tral, an upside reversal is in the cards. When the big money starts pushing the stock down while the small money is flat or buying, a downside reversal is more likely. Pascal compares his method to dropping down to the cell level and predicting the movement of the entire organism from the behavior of in- dividual cells. He first described his concept of Effective Volume in the interview for my book Entries & Exits, but he goes much further in his new book. The author introduces another key concept, which he calls Active Boundaries. His research shows that the group of professional traders in any given stock is relatively stable and they shoot for relatively steady gains. When the returns from a stock over a period of time reach their Up- per Active Boundary, the expectations for a further rise diminish and a xi
  13. 13. fm JWBK129-Willain March 18, 2008 14:0 Char Count= 0 xii FOREWORD downside reversal is more likely. When a stock declines and hits its Lower Active Boundary, bullish expectations become high and the stock has a greater probability of an upside reversal. Numerous charts show how to catch reversals using these concepts. In addition to Effective Volume and Active Boundaries, Pascal describes several other concepts. He even pro- vides what he calls “more complex examples for a second reading.” Pascal has a very rare ability to stand apart from the crowd, to question accepted concepts, and to come up with new ideas. For example, while acknowledging his debt to my Force Index, he stands the original concept on its head by asking why not have a Weakness Index, and even suggests its formula. This book abounds with examples of Pascal’s unorthodox approach. For example, he addresses a commonly heard rule, “You must buy when everyone else is selling,” and writes: For me, this is a sure recipe for financial disaster. There are only two clear times when you should buy: 1. You buy when everybody else is buying, but you do it early in the trend. 2. You buy when everybody else has stopped selling. In other words, you buy when the supply of shares has dried up, when only a few shares are available for sale. You have to invest time and energy in reading this book. Pascal, like many original thinkers, follows his own train of thought, sometimes leav- ing less prepared readers behind. During the past year I have been receiv- ing the analytic e-mails in which Pascal shares his research into current markets. It took me a little while to catch on to these concepts, and I hope that e-mails from readers will prompt Pascal to offer both his software and his analyses to the wider public. Publishing a book is like giving birth to a baby. This baby will require a bit of nurturing to grow and become strong enough to stand on its own. The reader must keep in mind that technical analysis alone is not enough to enable one to become a successful trader. Money management is essential for controlling risks, and you need good record keeping to learn from your profits and losses. I expect the concepts of Effective Volume, Active Boundaries, and oth- ers in this book to become accepted by many serious traders. As always, the early adopters will reap the greatest rewards. —D R . A LEXANDER E LDER New York City December 2007
  14. 14. fm JWBK129-Willain March 18, 2008 14:0 Char Count= 0 Acknowledgments f the Japanese government had not offered me a scholarship to study I applied mathematics in the 1980s, I never would have been able to even think about creating new tools for the stock market. If my friend Bob had not advised me some years ago to study technical analysis and buy Dr. Alexander Elder’s book, I would certainly by now be leading another life. If Dr. Elder had not recognized the novelty of my approach, and had not written about it; if he had not first introduced me to his own agent, Ted Bonanno, who helped negotiate the publishing contract, and then to Matthew Kushinka, my copy editor, who helped me find the proper flow of words in the English language; if Dr. Elder had not advised me on the book structure, the style, the title—even the look and feel of the cover— this book, frankly, would not exist. I am truly grateful for Dr. Elder’s help, especially considering how busy he is. I also want to thank the four early readers of this book: Bob Grush, from the United States; Barry Silberman, also from the United States; ´ ´ Frederic Snoy, from Belgium; and Thanassis Stathopoulos, from Greece. These four readers are independent traders who continuously look at im- proving their trading. Their comments and suggestions were of immense help to me, and I will always be grateful to them for their support. The last word is for my loving wife and life partner Michiko. Thank you for your continuous love and support. xiii
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  16. 16. intro JWBK129-Willain March 15, 2008 15:38 Char Count= INTRODUCTION Revolution Is at Your Doorstep n the eighteenth century, a Japanese rice trader named Munehisa I Homma noticed that it was possible to predict the evolution of prices by studying certain patterns of past prices. He invented what is now called candlestick analysis, still one of the most widely used technical analysis tools. He assumed at that time that current prices represent all known in- formation about the markets. This hypothesis is still shared by many pro- fessional traders, although we will see how limited it can be. In the twentieth century, many improvements in technical analysis appeared as new ideas emerged. These include Fibonacci retracements, Elliott wave analysis, moving average convergence/divergence (MACD) lines, and stochastics, to name a few. In 2001, lightning struck, but it went largely unnoticed. Why? As has often been the case throughout history, this revolution was the natural re- sult of a change that had different causes. Everybody noticed the change, but very few noticed the revolution. It was similar to Louis Pasteur’s dis- covery of microbes. That was a revolution, but the real change that made that revolution possible was the invention of the microscope. The change that would bring about a revolution to the technical analy- sis of stock trading was decimalization. It happened on April 9, 2001, when traders began to measure stock prices to the penny instead of in sixteenths of a dollar (or 6.25 cents). The objective was to make the stock price fluctu- ations easier for the general public to understand (thereby attracting more retail investors), as well as to reduce the spread cost. On the contrary, as we will see later, this change had a large impact on the way institutional investors play the market. Decimalization killed market visibility and, as 1
  17. 17. intro JWBK129-Willain March 15, 2008 15:38 Char Count= 2 VALUE IN TIME some believe, may have encouraged price manipulation. At the same time, decimalization allowed the precise detection of traders’ movements. What you will find in this book is not just one tool, but a complete set of revolutionary tools. These tools are based on how market players act—not on their behavior or on their potential reactions, but on their real, tactical moves. These tools are so powerful that I believe they will eventually be programmed into your favorite stock-trading platform. You probably know that kids learn new languages much more quickly than grown-ups do. An adult’s brain is already formed (the synapses are already connected), so changing the brain takes more than just in- stalling some new wiring. Similarly, it will be easier for beginning traders to read and understand this book than for confirmed traders. Most con- firmed traders have years of experience that have crystallized their habits; they have automatisms that follow given patterns and chart formations. Bring them a new idea, and doubt will set in, endangering their whole trading system. However, if you are not already set in your trading ways, if you are not a monk who comes out of his cell to pray to the gods of trading at specific hours, then you will greatly enjoy this book. I will lead you down unexpected paths to a complete new vision of stock trading. Since the time I started doing technical analysis, I have been awestruck by the specific art of charting and chart interpretation. There are so many superb books on the market explaining how to interpret chart pat- terns. When I try to interpret chart patterns, I feel like an amateur musi- cian who reads an unfinished sheet of music and tries to figure out how it could develop into a full concerto. Technical analysis has become a true art form, and I am thrilled when I meet artists who have mastered their art. Unfortunately, these great artists are on the verge of extinction. With the advent of computer trading and with the appearance of new tools such as those presented in this book, it is clear that traditional chartists will soon be forced to adapt in a new technical environment. In fact, everybody will have to adapt. The markets will be very harsh to those who do not. At the outset of this book, I would like to thank one of the great artists in chart reading: Dr. Alexander Elder. I came to technical analysis after I read two of Dr. Elder’s books: Come into My Trading Room and Trad- ing for a Living. I applied his methods, but even if I turned a good profit, I was not totally satisfied. I first tried to improve upon Dr. Elder’s meth- ods, but soon I realized that I had to start from scratch. I came up with a set of concepts and tools and developed them into a full trading method. I sent Dr. Elder a technical paper that explained my tools, and we met in Amsterdam. I was a bit nervous when we met: Would Dr. Elder listen to me? Would he like the ideas? To interest Dr. Elder in my work, I even told him that my method was a continuation of his work, when the truth was
  18. 18. intro JWBK129-Willain March 15, 2008 15:38 Char Count= Revolution Is at Your Doorstep 3 that even if I had learned the basics of technical analysis through his in- credibly eye-opening books, I was coming up with totally new concepts. For 30 minutes I presented my tools to Dr. Elder, while he asked for more information: Show me this and that. How do you calculate this or that? How do you get your data? I replied, “Just as you wrote in your book,” or “It is like the method you explain in your book.” But Dr. Elder looked at me and said in a deep baritone, “Noooooo . . . this method stands on its own feet.” I was indeed lucky that Dr. Elder had looked at my tools the way a doctor diagnoses a patient—by concerning himself with the facts. Later, when Dr. Elder visited me in Belgium, he told me that I should not be so humble about my method. Instead of introducing it in a sort of technical manual, I should call it what it is—a revolutionary method—and explain it in terms that are as simple as possible. He then went through the structure of this book, simplifying and reorganizing it to make things easier to understand, and advising me on the types of figures I should use and how to present them. When I told him that he should become coauthor of the book, he then replied, “Noooooo . . . it is not my method. Just write ‘Thank you, Alex’ somewhere in the book. That’ll do it.” Well, here you are, Alex: Thank you! WHAT IS THIS REVOLUTION ABOUT? First, I need to say that I am a dumb engineer, of sorts: I keep asking dumb questions, and I will continue to ask those questions until satisfactory an- swers are found that are also experimentally proven to be correct. Here are a few questions for which I could not find satisfactory an- swers in the literature: r How can you find out what institutional players are doing? Are insiders buying or selling? r How can you see that news is coming? r When is a stock cheap? When is it expensive? r Why do trends exist? Where do they come from? r What is the supply/demand equilibrium? This book is therefore about finding out what insiders are doing, what large funds are doing, what traders’ expectations are, and how the equilib- rium between supply and demand evolves. It is also about understanding when large funds are moving in and will eventually establish a new price trend, as well as knowing what buying power is necessary to support a trend, what will break trends, and when trends will be broken. In short, it is about reading the markets instead of guessing about them.
  19. 19. intro JWBK129-Willain March 15, 2008 15:38 Char Count= 4 VALUE IN TIME Traditional charts look very complex, because they are based mainly on prices. It is always difficult to make a decision based on one single piece of information (price), even if a price chart is supposed to include all the information about the market. The complexity lies in the guess- work, something at which traders need to become skilled if they want to be good traders. Many books talk about large funds as the “smart money.” Smart money is a term I have a hard time accepting, because it implies that the individ- ual trader is not smart. I prefer to say that information leaks and price ma- nipulations are routine occurrences in the markets. The objective of these leaks and manipulations is to take advantage of others. I would not call that smart. The tools that I developed will not allow you to become smart in the way that most traders define it. But they will allow you to see through ma- nipulation. You will become smarter, then, if you learn to see the markets more clearly and if this transforms you into a better trader. I disagree with people who reduce the market to a competition be- tween large players and individual traders, or who believe that market makers are behind the price moves. The market is much more complex than that, with an increasing number of connected, online traders scattered around the world, with 50 percent of the trades being computer-generated, and with large players often moving in opposite directions. You will, however, have to keep the following point in mind: The new tools for reading the market that I show you will not enable you to read the market exactly, all the time, and forever. Markets evolve, and I believe that all tools for analyzing the markets must evolve, too, including mine. HOW THE BOOK IS ORGANIZED This book is divided in two regular parts, followed by a bonus section. The first part describes in detail the four new tools that I developed in order for each of them to find a solution to a specific problem. The second part integrates the various tools into trading strategies, and I show what works and what does not for either retail players or fund managers. Part Three, the bonus section, shows how to adapt the tools to sector analysis. Part One: The Set of Tools That Will Change Technical Analysis I developed the sets of tools presented in this section because I needed them for my own trading. Each tool addresses a specific issue with only one goal in mind: to better understand the market. I am convinced that
  20. 20. intro JWBK129-Willain March 15, 2008 15:38 Char Count= Revolution Is at Your Doorstep 5 these new methods of measuring the market have the power to change technical analysis as we know it today. The industry will be slow to adapt, but in the end, I believe that the tools that provide a better measure of the market forces will prevail. Chapter 1: Effective Volume: An Open Window into the Market In Chapter 1, I show that the monitoring of the volume involved in small price changes from one trading minute to the next, which I define as the Effective Volume, is a very good tool to detect tactical moves by in- siders and large players. The Effective Volume tool is excellent for detect- ing trendsetters and often allows the detection of coming price changes. I also review in comparison how traditional tools use volume data. Chapter 2: Price and Value: The Active Boundaries Indicator Chapter 2 deals with the monitoring of price trends. It is based on the hy- pothesis that the group of active traders who follow a stock is relatively stable and that their automatic trading tools use buy/sell strategies that do not evolve in time. The Active Boundaries indicator takes advantage of this stability to capture trends between boundaries of expectation: The price of a stock has a great probability to reverse up when it hits the Lower Bound- ary (where expectation is the highest) and to reverse down when it hits the Upper Boundary (where expectation is the lowest). Chapter 3: When Volume Diverges from Price In Chapter 3 I show that the historical comparison of price trends to Effective Volume trends al- lows detecting, for a specific stock, thresholds that define levels of high ac- cumulation or distribution. This Divergence Analysis, after being adjusted for volatility discrepancies between price and volume, produces buy and sell signals that prove to be very effective. I then show how the combi- nation of Active Boundaries and Divergence Analysis can lead to a set of trading rules that could be combined to form a trading strategy. Chapter 4: Supply and Demand: The Key to Trading Chapter 4 takes a hard look at the supply/demand equilibrium as the major market force. This study leads to the presentation of the Supply Analysis tool. The Supply Analysis tool is based on the calculation of the probability that a share will be offered for sale, depending on the price at which it was bought, the time elapsed since it was bought, and the price evolution since then. I then show in practical examples how the Supply Analysis tool, combined with the Effective Volume tool, can very effectively measure the supply/demand equilibrium and therefore lead to winning trades. This chapter then moves on to study how funds play in an illiquid envi- ronment. It shows that funds have great difficulty making money, primarily
  21. 21. intro JWBK129-Willain March 15, 2008 15:38 Char Count= 6 VALUE IN TIME because of the large size of the positions they must take. Finally, we dis- cover that markets are very efficient and that therefore price manipulation by funds is not likely to occur. This leads us to the conclusion that tradi- tional funds will not be able to beat the market. Part Two: Trading Strategies After developing in the previous section a set of new tools that can be used independently, this section shows how these tools can be combined into various trading strategies. These trading strategies are tested against a buy/hold trading method not only in terms of risk/return balance, but also in terms of the total efforts that a trader must invest in order to sort out the best trading opportunities. Chapter 5: Performance: The Risk/Return Balance Chapter 5 shows that at the level of the trading strategy the risk/return balance is best measured using: r For the risk: the expected monthly loss transferred (MLT) by the trad- ing strategy to the portfolio. r For the return: the yearly expected return (YER) of the trading strat- egy. A performing trading strategy must produce a YER higher than that produced by a standard buy-and-hold strategy. We will also see in Chapter 5 how the profit target, the stop loss, and the time limit parameters can be used to manage an opened trade. Chapter 6: Automated Trading Systems Chapter 6 first reviews the alert and production screens, two information displays used to alert the trader to the evolution of a set of stocks. These two screens summarize the material covered in Chapters 1 through 4. Chapter 6 then combines the tools introduced in Chapters 1 through 4 into various trading strategies. We gradually discover the characteris- tics of the three pillars of good trading strategies: the discovery of value, the selection of the right buying trigger, and the management of the trade evolution. Part Three: The Bonus Section This part is called a bonus section because it opens the door to the under- standing of different facets of trading using the trading tools introduced in Chapters 1 to 4.
  22. 22. intro JWBK129-Willain March 15, 2008 15:38 Char Count= Revolution Is at Your Doorstep 7 Chapter 7: The Market Is a Two-Way Street: Shorting Strategies After explaining the “tick test” rule, Chapter 7 studies how the various tools can be used for shorting strategies. Chapter 8: Market and Sector Analysis Chapter 8 shows how the application of the Active Boundaries tool to the general market trend can help in determining when the market is overpriced. It then studies how a modified version of the Effective Volume tool can be used to study sector movements. READY FOR THE REVOLUTION The revolution of decimalization is here to stay. The only way that investors and traders can avoid becoming victims of insiders and manipulators is to use techniques that detect their moves. This is why I believe that tools such as those I present in this book will be widely used in the coming years. You will see that the different concepts introduced in this book are very simple in nature. The mathematics may look complex at first, but in fact it is mostly addition, subtraction, multiplication, and division. It is im- portant that you understand what the math represents, what it measures, and how you can take advantage of what it tells you. But it is not the math that is doing the trading; it is the trader.
  23. 23. intro JWBK129-Willain March 15, 2008 15:38 Char Count=
  24. 24. c01 JWBK129-Willain March 25, 2008 7:0 Char Count= PART ONE The Set of Tools That Will Change Technical Analysis
  25. 25. c01 JWBK129-Willain March 25, 2008 7:0 Char Count=
  26. 26. c01 JWBK129-Willain March 25, 2008 7:0 Char Count= CHAPTER 1 Effective Volume An Open Window into the Market hen you are considering a stock to trade, you have to view yourself W as a doctor treating a patient. You have three points of view to help you in your diagnosis: 1. The patient’s general condition: age, gender, any preexisting condi- tions, regular exercise or not, smoking or heavy drinking, and so on. 2. The patient’s symptoms: pain, fever, swelling, and the like. 3. The patient’s internal examination: a blood test, a scan, an X-ray, and so on. When analyzing a stock, you may think that the general condition is the fundamental analysis: earnings, profit growth, and so on. It may disappoint you to learn that these are only external measures of value. Value itself is useless if not compared to how it is priced. How value is priced is also virtually useless if you do not know what the expectation of shareholders is. Indeed, being a shareholder means possessing equity (value) for which the shareholder expects a return. You will understand in Chapter 2 that the general condition of a stock is partly represented by its price trend. You will often see a price mov- ing above and then below its price trend, indicating the evolving per- ception of value. Good trading requires you to catch this perception of value. I translate it into the measure of the expectation of active traders. You need to position your trades in harmony with this expectation: buy 11
  27. 27. c01 JWBK129-Willain March 25, 2008 7:0 Char Count= 12 VALUE IN TIME when expectation is high, and sell when it is low. Chapter 2 explains this expectation concept and how to measure it. It is my first pillar for success- ful trading. The second thing to look for when diagnosing a stock is its symptoms. Today’s technical analysis is still performed at the level of the symptoms: Traders like to catch trends and their reversals, they will look for over- bought and oversold situations, they will search for crowd movements, they will examine the demand/supply equilibrium, and so on. These traders are like doctors who look at a fever and know that after a few days the fever should dissipate. These traditional analysis tools are very useful if you mas- ter the art of interpreting them. Traders, like doctors, need a fair amount of experience to become truly skilled. Only then will they be able to see in the charts where a market or an individual stock is heading. These traditional tools require skills, training, and thinking. The great majority of traders use these tools with end-of-day data and react in unison during the following trading session. The “doctors” will see similar symp- toms and will prescribe similar treatments (though this is not always the case). I also use these traditional technical analysis tools, because it is crit- ical to see what others see to know where the technical analysis will push the crowd of traders. A doctor who has a doubt about a patient’s diagnosis will order a blood sample to be analyzed; the doctor can then diagnose the disease and pre- scribe the necessary medicine. Now, suppose that it were possible for a doctor to insert a tiny mi- croscope inside the patient’s body, and that this microscope had a wire- less communication with the doctor’s health monitoring station. The doc- tor could then monitor the fever not only after it appears (when the patient has already become sick), but before the fever appears, by monitor- ing any conditional change occurring at the microscopic level. The doctor could sort those changes and take into consideration only those that might cause a fever. Of course, this capability doesn’t yet exist in medicine. Sim- ilarly, what is lacking in today’s technical analysis is a way to detect micro changes that are strong enough to propagate over time into a full-blown sickness. A very useful tool that I present in this book therefore allows traders to reach what might be called the cell level. Going down to the cell level does not necessarily mean analyzing each transaction, looking over the trading book size, or studying all the coming orders. You need to look at the mi- crobes through your microscope, but remember that you are more inter- ested in seeing their propagation than their mere existence. When Pasteur discovered microorganisms such as viruses and bacteria, it was not finding out they existed that revolutionized medicine but rather the interpretation
  28. 28. c01 JWBK129-Willain March 25, 2008 7:0 Char Count= Effective Volume 13 of how these organisms work. This interpretation led the way to vaccines that changed our everyday life. I love the work of Russian Nobel Prize winner Dr. Ilya Prigogine and his theories of dissipative structures. I have to confess that it was when I was looking for a way to discover a new tool that I remembered my readings of Prigogine during my student days. Although these theories would not apply to understanding how the stock market works, I found the principles strikingly close to how I believe the stock market functions. The work of Dr. Prigogine states that the dissipation of matter or energy is usually linked to the ideas of efficiency loss and to the evolution toward a larger disorder. However, far from the equilibrium of a structure, the dissipation could be at the origin of new states of matter. In short, life was created by dissipation that brought a system far from the equilibrium and forced it into a new state of order. Prigogine states: Far from the equilibrium, a state of operation can look like an orga- nization because it results from the amplification of a microscopic deviation that at “the right timing” has privileged a reactive behav- ior as opposed to other reactive behaviors that were also possible. The individual behaviors can therefore in certain circumstances have a decisive role. —Translated by the author from La nouvelle Alliance, by Ilya Prigogine and Isabelle Stengers (Paris: Gallimard, 1979), page 237. As you may now understand it, the market may be moving en masse, and this pattern has been greatly amplified by the advent of the Inter- net and fast communications. However, I will show you that many mar- ket movements are started at a much lower level and that the broad price trend changes are often triggered by only a fraction of the volume exchanged. Figure 1.1 shows the analogy between the stock market evolutions and the evolutions of an organism. An organism that is in a state of equilibrium first needs to be put out of equilibrium by an external trigger. This external trigger is strong enough to generate a micro change. If this trigger repeats itself for a period of time, it can propagate the change to the whole organ- ism, which will then enter into a new state of equilibrium. I am not saying that we have to forget traditional technical analysis, but rather that traditional technical analysis is less and less adapted to fast- moving markets where information and manipulations are the basis of the market movements.
  29. 29. c01 JWBK129-Willain March 25, 2008 7:0 Char Count= 14 VALUE IN TIME Living Stable Organism Stock Organisms Market Strong trigger Strong volume Micro change Instability Price change Spread with time Spread with time Organism with a different stablility FIGURE 1.1 Change in market equilibrium. The price of a stock goes from one state of equilibrium to another. This change has triggered an abnormal increase in volume of transactions, one that is strong enough to trigger micro price changes whose spread will force a change in equilibrium. TRADERS GET A SECRET NEW TOOL: A BRIEF INTRODUCTION TO THE TRADING MECHANISMS AND THE MARKET PLAYERS Before explaining how things changed in 2001, I would like to point out three basic rules that govern the largest stock markets (NASDAQ, New York Stock Exchange, etc.): 1. The price precedence rule says that if you offer to sell a stock at the lowest price, your offer will be executed first. (If simultaneously John offers to sell his shares at $10, Jim at $10.01, and Martin at $9.99, Martin’s order will be executed first.) This guarantees that buyers also get the best price for the stock they purchase. Buy orders that offer the highest buying prices are also executed first. 2. The time precedence rule says that buy or sell orders that have the same price are ranked in their order of submission: The first to arrive is executed first. (If John offers to sell his shares at $10, and five seconds later Martin also offers his shares at $10, John’s order will be executed first, followed by Martin’s.) 3. A lesser-known rule is called the public order precedence rule. This rule states that members of a public exchange cannot execute their own orders ahead of orders from the general public that are standing at the same price. This rule was created to increase investor confidence that members of the exchange will not use their superior information to their advantage by trading ahead of the public.
  30. 30. c01 JWBK129-Willain March 25, 2008 7:0 Char Count= Effective Volume 15 These three rules are applicable for orders only when they reach the market. However, before reaching the market, some orders go through a broker. The broker can just forward the order, or can take advantage of it and trade for himself ahead of the client’s order. This is seldom the case, but dishonest brokers do exist, and the bad behavior of a few is finally pushing human beings out of the loop in favor of electronic order-routing systems. As brokerage houses get a commission on each transaction, some have found out that it is more profitable to trade their clients’ accounts of- ten, despite the fact that eventually they bankrupt their own clients and lose them. This reminds me of a friend who once told me that he had an e-mail exchange with a trading company in the United States; this company was ready to trade his account and, besides the traditional commissions on each transaction, take only 10 percent of his profits as commission. My friend thought that it was a good deal. Indeed, since he did not have to pay any management fee, he believed that this trading company would try to maximize its own profit, which was linked to my friend’s profit. My friend even asked me if I wanted to invest with him. I had to refuse, because I do not let other people manage my money. After only a few months, the first $25,000 he tested in that account had been reduced to almost nothing. He told me at that time that he was not very happy, but that he was calling the trading company on a regular basis; apparently they were always willing to give him an explanation on why they lost his money. Still later, when I met my friend again, he explained to me that after losing his first $25,000, he really wanted to get his investment back. He decided to get “really tough” with the trading company and gave them one last chance—he put in an- other $12,500. I remember telling him at the time that if the manager of his account was truly looking for a 10 percent profit, he never would have let the account go bust and he would certainly never have accepted my friend’s second investment. Why? The manager would have had to make a $25,000 profit to compensate for the first loss even before being paid one cent out of any profit from the additional $12,500. I advised my friend to take out whatever he could, because he was probably the victim of account churning, which is the term for when trading companies generate as many commissions as possible with useless trades. My friend did not follow my advice and thus learned an expensive lesson, losing his subsequent $12,500 investment. How Decimalization Changed the Markets Before 2001, prices were quoted in sixteenths of a dollar. Suppose you wanted to buy 1,000 shares of a stock whose bid price was $10.1875 and
  31. 31. c01 JWBK129-Willain March 25, 2008 7:0 Char Count= 16 VALUE IN TIME whose ask price was $10.25. If there were liquidity at $10.25, you could either (1) get your shares at $10.25 (for a total amount of $10,250) or (2) place a bid at $10.1875 (for a total amount of $10,187.50) and wait for your bid to get filled, hoping that nobody would bid higher than you, buy all the available shares at the ask, and consequently push the price up. The spread cost—the difference between the ask (the best price offered by sellers) and the bid (the best price offered by buyers)—was rather high at $0.0625; for 1,000 shares, the difference between placing the order at the ask and plac- ing it at the bid was $62.50. This high cost would have pushed buyers to place their orders at the bid and sellers to place their orders at the ask. Because of the time precedence rule that prioritizes the execution of or- ders, traders would place their orders early enough to be executed first. As a consequence, you could have market visibility and guess what large play- ers wanted to do. Indeed, Table 1.1 shows the order size for the bid and the ask before decimalization. Another consequence was that the price did not change much, since it took quite a large volume to move the price up or down by one tick (the smallest level of price change between the bid and the ask). Before decimalization, a tick was one-sixteenth of a dollar, or 6.25 cents. We see in Table 1.2 a similarly sized order book after decimalization. It shows 20,000 shares on the bid, but distributed between $10.19 and $10.13. It also shows 22,000 shares on the ask, distributed between $10.20 and $10.25. As a trader, suppose that you want to order shares at the bid. In Table 1.1, you are competing against 20,000 shares. If you wait longer, the bid could increase, and your chances to get shares at $10.1875 could diminish. Therefore, you will be inclined to rush your order in. However, if you want to buy shares at the bid in Table 1.2, you are competing against only 500 shares. You now have less motivation to place your order at the bid, since competition is not showing up. You prefer to keep your hand closed like a good poker player. If you are lucky enough, someone will sell 600 shares at market price and the bid will be lowered one cent. This may allow you to get your shares at a cheaper price. Book of Orders TABLE 1.1 (before Decimalization) Buyers Sellers Bid Volume Bid Ask Ask Volume 20,000 $10.1875 $10.25 22,000
  32. 32. c01 JWBK129-Willain March 25, 2008 7:0 Char Count= Effective Volume 17 TABLE 1.2 Book of Orders (after Decimalization) Buyers Sellers Bid Volume Bid Ask Ask Volume 500 $10.19 $10.20 10,000 3,000 $10.18 $10.21 3,000 5,500 $10.17 $10.22 7,000 1,000 $10.16 $10.23 300 5,000 $10.15 $10.24 700 4,000 $10.14 $10.25 1,000 1,000 $10.13 The book of orders lists the prices at which buyers and sellers are ready to trade as well as what volume they want to trade. The spread is the difference between the best bid price (here, $10.19) and the best ask price (here, $10.20). In this example, the spread is $0.01. A buyer wanting to buy 100 shares may buy them at the bid for $10.19 per share and wait in line until the existing bid order of 500 shares is first executed, or may pay one cent more and have the order executed instantaneously at the ask for $10.20. Furthermore, if you need to buy 12,000 shares in Table 1.2 and you place an order at the ask, the price will move up one tick to $10.21. This may be undesirable, especially since you would still like to buy another 100,000 shares at a good price. If you put large buy orders at the bid, you will show your hand to the market and attract other buyers. The cheapest course of action would be to buy 9,500 shares at the ask, then sell 600 shares at the bid. The ask price would stay unchanged, but the bid price would fall one cent to $10.18. This would eventually cause sellers to lower the ask to $10.19, allowing you to buy your next set of shares at a lower price. It is a legitimate price manipulation that funds need to use in order to accumulate or distribute shares during sideways trading ranges. In Chapter 4, we will see if this manipulation is common practice. In addition to this, program trading would automatically use these tac- tics to dispose of or purchase large blocks during sideways trading ranges, making sure that the price stays in the trading range until the strategic move is finalized. In conclusion, we have seen that decimalization killed market visibility while favoring price manipulations. Fortunately, the Effective Volume tool that I present in Chapter 1 provides a way to see through tactical moves by large players. It allows all other traders to analyze the repetitive market tactics and show the underlying strategic decisions of large players. The Effective Volume tool does not imply that these strategic de- cisions are correct and that you need to trade in the same direction.
  33. 33. c01 JWBK129-Willain March 25, 2008 7:0 Char Count= 18 VALUE IN TIME However, knowing what large players are doing is key to helping your trading decisions, whether you are a retail player or a competing institu- tional player—especially if you have a correct measure of value. The Active Boundaries tool that I present in Chapter 2 will allow you to obtain a very accurate measure of value. Since I began using the Effective Volume tool, one of my trading prin- ciples has been not to trade against large players. This is not to say that I always trade with the large players, but I am not fool enough to trade against them. How Large Funds Adapted to Decimalization A large fund has the dual advantage of size and power, but it also has limi- tations. Funds provide liquidity to the markets, and the system is designed to allow them some flexibility. The decimalization rule served them this flexibility on a silver platter. This rule was initially conceived as a way to attract private investors and lower the spread costs, but it was in fact an im- plicit authorization for large funds to manipulate markets. Indeed, before decimalization, if a fund wanted to lower the price of a stock, it had to sell at the bid enough shares to take out all the outstanding buy orders. Since the spread cost was high, all players entered their order in advance (first come, first served), and it was easy to see what large players wanted to do. Market manipulation at that time was quite costly. (For example, you had to sell perhaps 10,000 shares at a spread cost of $0.0625. This meant that if in fact you wanted to lower the price in order to buy a larger quantity at a lower price, you would have to purchase these 10,000 shares back $0.0625 higher. The manipulation would have cost you $625.) Decimalization, though, lowered the spread cost, and therefore freed large players from disclosing their orders. This greatly reduced the size of the order book, allowing anybody with just a few hundred shares to in- crease or decrease the stock price. Typically, these days, if you have 1,000 shares, you can easily push the price down by one cent, at a cost of 1,000 × $0.01 = $10, which is 60 times less than before decimalization. I have no proof that markets are constantly manipulated. However, if a service sud- denly costs 60 times less than it did the day before, you can be sure that this service will be used more often. New Tools Are Necessary Further on in this chapter I make detailed comparisons of the different tools that are used to study the price/volume relationship, but what I want to stress here is that a tool is an instrument that you are using to take a
  34. 34. c01 JWBK129-Willain March 25, 2008 7:0 Char Count= Effective Volume 19 measurement. That measurement gives you some clue about the underly- ing reality. I like to compare trading a stock through technical analysis to the ac- tions of an engineer who is in charge of a petroleum extraction rig. This en- gineer is responsible for digging a deep hole and eventually hitting a target. When drilling, the crew will encounter different types of ground texture; re- sistance and friction will increase. They will also encounter changing heat and pressure conditions. The engineer knows by experience that they will need more than one instrument to understand what is happening to the rig deep down in the hole. Similarly, traders need to use different tools when analyzing a stock. The market is very complex. It is, of course, different from what it was 100 years ago, but it is also more complex than even 15 years ago. Just look at three key changes that have happened since then: 1. Communication speed has resulted in very quick price adjustments to news. Markets are becoming more efficient, but also crowded with many retail investors enjoying online communication. 2. Decimalization has changed the tactics of large players. 3. Hedge funds are bringing liquidity but also volatility (very large swings of price and volume). A trader needs tools that can handle these changes. Such tools there- fore need the following characteristics: r The tools need to catch the strategic moves using an analysis of the accumulation/distribution tactics. Usually, institutional investors frag- ment one large order into many small orders that can then be sent undetected—this is called order fragmentation. Each small order will then be executed in one or more market transactions. Although data related to each transaction and each fragmented order is available, the tools need to “reconstruct” the fragmented orders, using minute data so that traders can have a better understanding of what institutional players are up to. r The tools must be able to filter the noise out of the important signal. (We will see later in the chapter that only 25 percent of the total ex- changed volume is responsible for 75 percent of the price changes. You’d better know the direction of the 25 percent and not move against the direction of these changes.) r The tools must tell you if the moves of the large players are significant enough to induce a price change or to make or break a trend. r The tools must allow you to make volatility adjustments between price and volume, which carry very different levels of volatility.
  35. 35. c01 JWBK129-Willain March 25, 2008 7:0 Char Count= 20 VALUE IN TIME r The tools must show you what the position and expectation of other active traders are, because you will need to buy cheap—and a cheap price will be harder to find if everybody else expects the share price to decrease and is ready to sell. A cheap price is found when the last seller has finished selling and new buyers come in with a high expectation for the price to increase. Finally, wouldn’t it be nice if your computer scanned hundreds of stocks, applying all these new tools and giving you buy and sell signals? VOLUME THAT MOVES THE MARKETS When I started this work, I was almost completely convinced that large players were mainly responsible for stock price movements, because of the large size of their trades. Therefore, monitoring the movements of large players seemed to be the best way to monitor the whole market. My con- cern was to find out when institutional investors were moving in or out of stocks. The analogy with Dr. Ilya Prigogine’s work was telling me that I needed to do three things: 1. Measure the impact of volume changes to price changes at a level that was as close as possible to the transactional level. 2. Separate large from small volume. 3. See the evolution of such volume. Therefore, I needed to be able to compare this evolution between fixed periods of time. I was looking for a tool that could do these things. Because I am lazy, I tried to find an already existing tool, one that I could use right away. I found two categories of tools: the “tick volume” tools and the “end of day” tools. As we will see later in this chapter, both types of tools have their own limitations and therefore neither could meet my needs. Still wondering why nobody had found an answer to an obvious ques- tion (“What are large players doing?”), I started to develop my own tools. In trying to answer that question, I realized that there are not that many different types of data to work with: on the time interval basis (1-minute, 5-minute, 10-minute), you can play with the open, high, low, and close of the price data, and add to it the volume data. On the transactional level, you have the order size, the execution time, the execution size, the price of execution, and some other minor information.
  36. 36. c01 JWBK129-Willain March 25, 2008 7:0 Char Count= Effective Volume 21 TABLE 1.3 One-Minute Data Open High Low Close Volume 9/25/06 14:27 $11.07 $11.07 $11.06 $11.06 5,889 9/25/06 14:26 $11.06 $11.06 $11.06 $11.06 200 9/25/06 14:25 $11.06 $11.07 $11.06 $11.06 28,335 9/25/06 14:24 $11.05 $11.06 $11.05 $11.06 18,131 9/25/06 14:23 $11.04 $11.06 $11.03 $11.05 33,188 9/25/06 14:22 $11.03 $11.04 $11.03 $11.04 3,298 9/25/06 14:21 $11.02 $11.04 $11.02 $11.04 29,658 9/25/06 14:20 $11.02 $11.02 $11.02 $11.02 17,825 9/25/06 14:19 $11.01 $11.02 $11.01 $11.02 11,351 9/25/06 14:18 $11.02 $11.02 $11.02 $11.02 40,889 9/25/06 14:17 $11.04 $11.04 $11.01 $11.02 14,015 9/25/06 14:16 $11.05 $11.06 $11.04 $11.04 13,802 9/25/06 14:15 $11.06 $11.06 $11.05 $11.06 32,536 9/25/06 14:14 $11.07 $11.08 $11.06 $11.06 16,399 9/25/06 14:13 $11.07 $11.08 $11.07 $11.07 20,041 Typical one-minute data format, including the minute opening price (open), the high of the minute (high), the low price of the minute (low), and the closing price of the minute (close). The last column represents the volume exchanged during that trading minute. I started with the raw one-minute data such as that displayed in Table 1.3. Because the trading day is 6.5 hours long, there is a maximum of 390 trading minutes. Table 1.3 shows a typical data set, each line representing one minute. More recent data are shown at the top of the table. As shown in Table 1.3, each trading minute has an opening price, a high price, a low price, and a closing price. This means that during a trading minute, traders have been buying and selling shares. The price variations between the low and the high indicate that such activity existed. These price variations are usually done tick by tick. Conventionally, upticks and downticks are tiny price movements that move the price up or down by one tick (usually one cent). Within one trading time interval of one minute, there can be several upticks and downticks. From time to time, a volume spike takes the price up or down several ticks at a time. I call price inflections the small price changes that occur between one trading minute and the next. Let’s call the volume that is responsible for a price inflection the Effective Volume. We will see later how to calculate it. Please note that for me a price inflection of one tick has the same weight as a price inflection of two or more ticks, at least to measure the up and down buying and selling movements.
  37. 37. c01 JWBK129-Willain March 25, 2008 7:0 Char Count= 22 VALUE IN TIME A price inflection indicates that the equilibrium between the bid and the ask was broken because of underlying market activity (traders pushing the price down instead of traders pushing the price up or vice versa). Dur- ing one trading minute, the equilibrium can be broken on one side and then suddenly reverse to the other side. This usually happens when buyers and sellers trade similar volume sizes with a similar determination. In the course of trading, suppose that an institution intends to place a large buy order. Either this large buy order will go as a block directly between institutions or that institution will have to buy from the market. Large orders placed at market usually push the price up. In order to go unnoticed, a large order has to be fractioned into tiny orders that will be brought to the market on a systematic basis. This must be done without triggering a new uptrend before the whole lot has been bought. This re- quires a careful tactical execution that involves a mix of order sizes and timing variations. Institutions either use special order-placing algorithms or obtain the assistance of a market maker. How to Detect Such Movements Only a fraction of the orders that reach the market are executed. Executed orders create transactions between a buyer and a seller. The buyer’s and the seller’s respective buy and sell orders are mutually filled. If you only study the transactions, it is very difficult to see the direction of these trans- actions. Because for each transaction there is a buyer and a seller, it is impossible to tell if sellers are stronger than buyers. The direction of the trade is indicated by the small price change that oc- curs on the transaction: If the price increased on the transaction, the buyer was stronger (pushed the price up). Otherwise, the seller was stronger. Be- cause institutions split up large orders into numerous small orders, study- ing the transaction size does not help in figuring out whether the transac- tion was generated by an institution. What we therefore need to do is study all the aggregated transactions within regular time intervals of one minute. The idea is to reconstruct the size of the original order by adding up all the transactions that occurred within one minute and to compare that number to the price variation. Let’s study this idea in one example: a large buyer. Let us suppose that an institution wants to buy 100,000 shares on the market of a stock that is trading 500,000 shares per day. The institution will probably have to use one of the following four tactics: 1. Place a large buy order at the bid. 2. Place regular small buy orders at the bid.
  38. 38. c01 JWBK129-Willain March 25, 2008 7:0 Char Count= Effective Volume 23 3. Place regular small buy orders at the ask. 4. Place a large buy order at the ask. Let’s study the consequences of such moves. 1. Place a large buy order at the bid. This is a passive strategy, since the institution has to wait for sellers to come to it. But, since regular buyers are still active, these players would need to bid the price up to get their shares. As a result, the institution will also have to raise its large bid, with the risk of starting a new uptrend. This method is ineffective for accumulating shares. It is easily detectable, since the large bid signals to the market that a large player is accumulating. 2. Place regular small buy orders at the bid. This is also a passive strat- egy, but the institution will not be easily detected. As we will see in Chapter 4, this strategy does not allow large players to take a signifi- cant position, and is therefore probably not often used. 3. Place regular small buy orders at the ask. This strategy is more active, because the institution is actively buying shares. This method requires that the institution have patience in its accumulation, to avoid price spikes that could trigger a new uptrend. However, because the buy- ing is regular during a short period of time, the supply of shares will momentarily dry up and the price will momentarily increase. The insti- tution needs to monitor these small price increases. If the small price increases trigger a change of key technical patterns, they could attract more buyers while the institution has not met its targeted number of shares. On small price increases, the institution must therefore either (1) wait for new sellers to come and push the price back down or (2) push the price back down by itself with a small sell order. Because of the statistical significance of the repetitive buying pattern, even dis- tanced buy orders placed at the ask form a pattern using the Effective Volume, which I explain in the next section. The visible pattern is that large volume will be more often linked to price increases than to price decreases. 4. Place a large buy order at the ask. This very active strategy is used only when several institutions are competing to get shares, or when an institution wants to trigger a price increase by signaling to the market that it is buying shares. This is easily detectable through the monitoring of the price trend. It should now be clear to the reader that what we need to analyze is not the situation at one point in time, but the regularity of the pattern during a set of consecutive, identical time intervals.
  39. 39. c01 JWBK129-Willain March 25, 2008 7:0 Char Count= 24 VALUE IN TIME Traditional Way to Calculate Shares Accumulation Larry Williams created a now widely used formula to calculate the accu- mulation/distribution (A/D) balance on daily charts. Figure 1.2 shows such a calculation. The principle is to weight the total volume exchanged during the day by the price gain/loss, divided by the price spread during that day. r Share accumulation means buying. r Share distribution means selling. The simple idea behind this is to say that if shares are exchanged dur- ing the day and the closing price is higher than the opening price, for exam- ple, the total result is considered positive: Buyers are stronger than sellers. This means that on average, there is share accumulation during the day. However, if the price spread during the day is very large compared to the gain, it means that traders have been fighting during the day. Therefore, the strength in accumulation of shares should be proportional to the extent of the fight. In Figure 1.2: r The gain = the outcome of the fight = $10.4 − $10.2 = $0.2. r The spread = the extent of the fight = $10.5 − $9.8 = $0.7. High $10.5 Close $10.4 Gain/Loss Spread Open $10.2 Low $9.8 FIGURE 1.2 Larry Williams accumulation/distribution example #1. Gain Accumulation = × Volume Spread $10.4 − $10.2 × 100,000 shares = 28,571 shares $10.5 − $9.8
  40. 40. c01 JWBK129-Willain March 25, 2008 7:0 Char Count= Effective Volume 25 r The number of shares shown by the accumulation calculation is therefore: $0.2 100,000 × = 28,571 shares $0.7 However, if the opening price had been $10.4 and the closing price $10.2, there would have been a loss of −$0.2, and we would have seen the same number of shares (28,571 shares), but on the distribution side. We can note two potential problems with this formula: The first problem is shown in Figure 1.3. Because the spread and the gain shown in Figure 1.3 are identical to the spread and the gain shown in Figure 1.2, the result of the accumulation/distribution calculation is identi- cal: 28,571 shares in both cases. However, some traders will tell you that the close of Figure 1.2 is stronger than the close of Figure 1.3, because the price in Figure 1.2 closed higher. Therefore, the share accumulation shown in Figure 1.2 is maybe more important than the share accumulation shown in Figure 1.3. This is why traders who calculate the accumulation/distribution of shares on the FIGURE 1.3 Larry Williams accumulation/distribution example #2. Gain Accumulation = × Volume Spread $10.1 − $9.9 × 100,000 shares = 28.571 shares $10.5 − $9.8 Accumulation as defined by Larry Williams is independent of the relative position of the gain within the high-low range.
  41. 41. c01 JWBK129-Willain March 25, 2008 7:0 Char Count= 26 VALUE IN TIME basis of price spread during a day will also look at where the close ended compared to the price spread. If the close ended near the high, they would conclude that the buying side had been stronger than the selling side. The second potential problem is a lesser-known one: manipulation of the opening price sometimes exists. A strong opening price may attract buyers, while a strong closing price may attract sellers. A fund that wants to sell a large number of shares could therefore try to set a positive tone by forcing a strong opening. In case of a different opening price, the Larry Williams accumula- tion/distribution formula yields quite a different result. Figure 1.4 shows that if the opening price had been $10.5 instead of the open of $10.2 shown in Figure 1.2, the Larry Williams formula would have resulted in a distri- bution of 14,286 shares instead of the accumulation of 28,571 shares calcu- lated in Figure 1.2. My message here is simply that in some cases, the opening price might be less valid as a parameter than the closing price. In general, methods that use end-of-day data could be more vulnerable to price manipulations, since they rely on fewer data points. The comments relative to Figures 1.2–1.4 have not been backed by any research data. The interested reader should refer to Larry Williams’ book Long-Term Secrets to Short-Term Trading. FIGURE 1.4 Larry Williams accumulation/distribution example #3. This method is very sensitive to opening price manipulations. In this case, an opening price at $10.5 instead of $10.2 results in a distribution of 14,286 shares instead of an accu- mulation of 28,571 shares. Loss Distribution = × Volume Spread $10.2 − $10.5 × 100,000 shares = −14.286 shares $10.5 − $9.8
  42. 42. c01 JWBK129-Willain March 25, 2008 7:0 Char Count= Effective Volume 27 Do Not Trade Like My Grandmother The classic technical tools that use the daily price changes and the daily volume are based on two assumptions regarding volume: The first assumption is the price repartition of volume. These tools sup- pose that the volume is regularly distributed at every tick between the low and the high prices of the day. Let us take the example of the company Tellabs on September 20, 2006. On that day, during trading hours, about 11 million shares changed hands. The Larry Williams accumulation formula gives: Opening price: $10.35 High price: $10.41 Low price: $10.05 Closing price: $10.29 $10.29 − $10.35 Distribution = × 11,000,000 $10.41 − $10.05 Distribution = −1,833,333 shares Based on this example, this means that at every tick between $10.05 and $10.41, 297,000 shares were exchanged (see Figure 1.5a) (11,000,000 divided by the difference between $10.05 and $10.41 plus 1 tick, since the subtraction eliminates one of the two ticks at the extremities—the tick of FIGURE 1.5a The linear volume repartition by price level. Linear volume reparti- tion by price level is the first simplification implied by technical tools that use daily price variations and volume.
  43. 43. c01 JWBK129-Willain March 25, 2008 7:0 Char Count= 28 VALUE IN TIME FIGURE 1.5b The real volume repartition by price level. The real volume reparti- tion by price level is very different from the linear repartition. the minute low price or the tick of the minute high price; between $10.05 and $10.41, there are therefore 37 ticks and not 36 as a normal subtraction would show). In reality, the volume exchanged forms an irregular pattern, as shown in Figure 1.5b. The second assumption is the time repartition of volume. The tradi- tional tools suppose that the volume is regularly distributed every minute between the open and the close of the trading day. In our example, this means that at every minute between 9:30 A . M . and 4:00 P . M ., 11,000,000 ÷ 390 = 28,205 shares have been exchanged (see Figure 1.6a). In reality, the daily buying and selling pattern clearly shows that volume came in spikes, and that a large proportion of the transactions occurred at the end of the trading day (see Figure 1.6b). The two assumptions made by traditional tools that use end-of-day data to calculate the accumulation/distribution of shares are so drastic that as a trader, I have little confidence in using these tools, although some traders may find them reliable. Indeed, one big characteristic of volume is that it comes in spikes. Typ- ically, you would see many transactions of 100 shares and then suddenly a single transaction for 10,000 shares, or a set of transactions that would fill many small orders. In short, volume has a very high volatility on a minute- by-minute level. On the day-by-day level, too, volume could jump 100 percent from one day to the next. This volatility is well known to traders whose mantra is “A price increase on a strong volume day is more valid than a price in- crease on a weak volume day.” This is experience talking, similar to my
  44. 44. c01 JWBK129-Willain March 25, 2008 7:0 Char Count= Effective Volume 29 Tellabs: Linear Volume Historam by Time, 09/20/2006 Number of Shares FIGURE 1.6a The linear volume repartition. The linear volume repartition by time level is the second simplification implied by traditional tools that use daily price variations and volume. grandmother’s advice when making jam: “If you close the pot when the jam is hot rather than when it’s cold, the jam will keep longer.” She was talking about what she knew from experience; she didn’t have to be knowl- edgeable about the microbiological phenomenon. Most of today’s traders still act in the markets like my grandmother did in the kitchen. They understand little about the trading mechanism, and few really are aware of what their trading tools are calculating or what their limitations are. Tellabs: Real Volume Historam by Time, 09/20/2006 Number of Shares FIGURE 1.6b The real volume repartition by time level. The real volume reparti- tion by time level is very different from the linear volume repartition.
  45. 45. c01 JWBK129-Willain March 25, 2008 7:0 Char Count= 30 VALUE IN TIME Do not trade like my grandmother made jam. You need to understand what is going on in the market that you trade. There are two ways to gain knowledge: 1. Invest time to study how the market works. I advise you to participate in one of the seminars that Dr. Alexander Elder gives, or even one of his weeklong trading camps. Not only do these courses give you a working structure, but they also help you to feel how the market is moving. You will gain knowledge and confidence. 2. Use modern tools that will tell you what is happening. EFFECTIVE VOLUME To define the Effective Volume tool, I applied three modifications to Larry Williams’ method. Let’s look at Figure 1.7, where we see the evolution of the price during one trading minute. We can see that the price evolved among five ticks: $10.00, $10.01, $10.02, $10.03, and $10.04. If we suppose that 5,000 shares were traded during that trading minute, Larry Williams’ formula would tell us that the share accumulation is: $10.03 − $10.01 Accumulation = × 5,000 = 2,500 shares $10.04 − $10.00 1. The first modification is to replace the open of the actual trading minute with the close of the previous trading minute. This modifica- tion looks at the volume that has a real impact on the price from one trading minute to the next. If the price increased, the Effective Volume will be positive. Otherwise it will be negative. FIGURE 1.7 Larry Williams accumulation/distribution.
  46. 46. c01 JWBK129-Willain March 25, 2008 7:0 Char Count= Effective Volume 31 2. If the close from the previous minute is lower than the low of the actual minute, the second modification is to replace the low of the current minute with the close of the previous minute. Similarly, if the close from the previous minute is higher than the high of the actual minute, then the Effective Volume method requires replacing the high of the current minute with the close of the previous minute. In our example, if we suppose that the previous close was at $9.99, we then would need to use that previous close in our calculation instead of the open of the minute (see Figure 1.8). This modification would give us the following number of shares being accumulated: $10.03 − $9.99 Accumulation = × 5,000 = 4,000 shares $10.04 − $9.99 3. A last small adjustment still needs to be done: When applying the mod- ified Larry Williams formula on small time intervals, it is necessary to add 0.01 to the top and to the bottom of the formula. The reason for this is that when shares are distributed between, for example, a low of $9.99 and a high of $10.04, it means that the shares traded at $9.99, $10.00, $10.01, $10.02, $10.03, and $10.04—six ticks instead of five (as would have been the case with the Larry Williams formula that sim- ply subtracts $9.99 from $10.04, which would equal $0.05 or only five ticks). Applying the three small modifications to our example, the Effective Volume calculation gives the following results: $10.03 − $9.99 + $0.01 Accumulation = × 5,000 = 4,167 shares $10.04 − $9.99 + $0.01 FIGURE 1.8 Modified Larry Williams accumulation/distribution.