In this thought-provoking work, David Aronson tests more than 6,400 technical analysis rules and finds that none of them offer statistically significant returns when applied to trading the S&P 500. This result, presented at the end of his work, is not disappointing to dedicated students of technical analysis who draw from the book not a new trading technique but instead take away a new, and more effective, approach to system development and trading. Those seeking the single best indicator or day trading pattern will be disappointed after reading Evidence-Based Technical Analysis, just as they will be disappointed in their trading until they advance beyond seeking the Holy Grail of Trading.
Most books and articles about technical analysis focus on applying a specific technique in pursuit of success in the markets. This one is different in that it outlines an entirely new process of thinking, and through the application of this new thought process, success can be attained. Part I of Evidence-Based Technical Analysis is called, "Methodological, Psychological, Philosophical, and Statistical Foundations" and Aronson uses this title as an outline to define the processes which should underlie system development.
The scientific method changed the world, and made the advances of modern society possible. Until now, technical analysis has been considered more of an art than a science to many practitioners and escaped the scrutiny of the scientific method. With recent advances in computing power and analysis software, it is now possible for virtually anyone to search through years of data and identify seemingly profitable trading rules. Aronson presents the scientific method, combined with the philosophy of science as explained by Karl Popper, as an antidote to this very real danger.
Well designed experiments in any scientific inquiry are based upon a verifiable hypothesis grounded in detailed observations. Popper contributed the concept of falsification to this framework, which readily lends itself to mechanical trading system design. As Aronson writes, "Popper's central contention was that a scientific inquiry was unable to prove a hypothesis to be true. Rather, science was limited to identifying which hypotheses were false."
In technical analysis, we can never prove that if the NYSE Advance-Decline Line reaches a new high, the Dow Jones Industrial Average will always be higher thirty days later. But, we can test this hypothesis to see if it is not true. This simple example illustrates the beginning of Aronson's scientific approach to the markets.
Many of the dangers of data mining and curve fitting are grounded in psychology, and Aronson thoroughly explains many of the common problems that can contribute to inaccurate observations. Carefully studying his sections on logic and psychology should lead to better market observations, which should lead to profitable systems.
The chapters on statistical analysis are worth more than the price of the book in itself. Aronson presents a clear primer on statistics, and leaves the reader with all they need to understand how to design a statistically valid experiment. In what may very well be a publishing first, he presents clear, detailed and understandable descriptions of bootstrap and Monte Carlo randomization methods.
This book is well-researched and presents actionable ideas to advance the study of technical analysis. Although none of the rules Aronson tested proved to be statistically significant, he helpfully devotes a section to explaining the limitations of his test results. Armed with this information, and the knowledge provided in the rest of the book, the thoughtful analyst can develop better insights into the market and perform better backtests to identify profitable strategies.
David Aronson's Evidence Based Technical Analysis ("EBTA") is a fantastic book, and one which our industry has sorely needed. It is a "How to Do Research" book that details the scientific method with regard to the markets. Everyone in the field should both read the book and practice what it preaches. But that won't happen, which is both bad news and good news. The bad news is that the vast majority of market traders who do not practice what the book preaches will lose money. The good news is that those who do will most certainly prosper. As the numbers of the former outnumber those of the latter, the few will earn a lot from the many.
The long (over 100 pages) psychology "preface" is extremely important to Aronson's body of work. I found it hugely interesting, but fear that others may not, or worse. In fact, the psychology preface itself indicates that this work will be reviled (my words) by the multitude. People do not like their sacred cows criticized.
The problem is that most market practitioners use methods with little or no scientific basis. Even if shown evidence of faulty logic, people continue to believe its validity. This is also true in the medical profession as Aronson illustrated and which scared the daylights out of me.
For anything to be scientifically testable, it must be possible to prove it wrong. However, many of the technical analysis disciplines cannot be defined. Thus they cannot be disproved. Consequently they have no scientific validity. They may have some anecdotal importance, but true science is lacking.
Let us say that one of the market gurus espouses that when the chart of XYZ resembles "Pattern A", the stock is destined to rally. To test that we have to define Pattern A and we have to define "rally", and we should provide some time parameters in which to work or fail. The trouble is that the guru cannot define any of that. But the guru still believes in his work, and all of the investors who pay monthly fees for his expertise believe it also. Anyone who criticizes the guru or the validity of Pattern A is looking to get flamed.
EBTA preaches that technical analysis research should be conducted like quantitative analysis research. Those who treat TA as a casual discipline will get casual results. The book is not an easy read, but it is an easier and much more interesting read than the "bible" of the CFA community, Quantitative Methods for Investment Analysis (DeFusco, et al.). I own both books and certainly consider EBTA more valuable than the CFA manual, worshipped by thousands. Don't expect to download all of Aronson's knowledge the first time - read it again. I did and learned more the second time through.
Aronson is meticulous and provides "service after the sale". I had recently traded emails with him about an article he had cited. He was prompt to respond and discus the implications of our expanded research. I have the feeling that he is like this with everyone.
In conclusion I have to say, that if you cannot do what EBTA preaches, at least get yourself a money manager who does.
Professor Aronson's book is a fascinating read for anyone frustrated with the current state of technical research and a must-read for those new to the field. I believe the Market Technicians Association should include it in its Chartered Market Technician curriculum.
After a few years of studying and using technical analysis, I was left with the distinct feeling that there was an elephant in the room: most of the methods used by market technicians haven't been rigorously examined for risk-adjusted performance. Elaborate and often contradictory theories and strategies have been presented by saying "my personal experience has been..." or something similar. Eventually, TA began to seem more a religious choice rather than a science of observing and predicting the markets (let alone successful investing).
Aronson's book follows a structure that is designed to break through generations of instruction from pontificating gurus. He discusses the reason TA's rules are suspect, provides a brief history of empiricism ("the scientific method") and then delves into descriptive and inductive statistics to move the field forward. Those readers fortunate enough to have an undergraduate background in philosophy and statistics will find the reading somewhat basic but the application of these fields to a critical appraisal of TA refreshing. Finally, he applies his rigorous testing to a large set of TA rules.
Key takeaway: The way to develop and test strategies going forward.
Product Details :
Hardcover: 544 pages
Publisher: Wiley; 1 edition (November 3, 2006)
Language: English
ISBN-10: 0470008741
ISBN-13: 978-0470008744
Product Dimensions: 6.3 x 1.6 x 9.1 inches
More Details about Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals 1st edition
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