Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals (Hardcover)

~ (Author)
Key Phrases: systematic price movements, immediate practical future, observed mean return, Monte Carlo, Law of Large Numbers, Dow Jones (more...)

Editorial Reviews

Review

"…his book is well written and contains a great deal of information that is of value…." (The Technical Analyst, May/June 2007)

Product Description

Evidence-Based Technical Analysis examines how you can apply the scientific method, and recently developed statistical tests, to determine the true effectiveness of technical trading signals. Throughout the book, expert David Aronson provides you with comprehensive coverage of this new methodology, which is specifically designed for evaluating the performance of rules/signals that are discovered by data mining.

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Product Details

• Hardcover: 544 pages
• Publisher: Wiley (November 3, 2006)
• Language: English
• ISBN-10: 0470008741
• ISBN-13: 978-0470008744
• Product Dimensions: 9 x 6.1 x 1.8 inches
• Shipping Weight: 1.9 pounds (View shipping rates and policies)
• Average Customer Review: 4.0 out of 5 stars  See all reviews (48 customer reviews)
• Amazon.com Sales Rank: #40,094 in Books (See Bestsellers in Books)

Customer Reviews

Most Helpful Customer Reviews

113 of 121 people found the following review helpful:

5.0 out of 5 stars Great book, November 12, 2006

By	Mike Carr, CMT (Cheyenne WY) - See all my reviews

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.

66 of 75 people found the following review helpful:

1.0 out of 5 stars There is better books available, December 23, 2007

By	F. G. J. Breytenbach - See all my reviews (REAL NAME)

This book doesn't test 6400 binary rules,unless you see a Price/Moving average cross with a period of 1 to 200 as 200 rules. I see it as 1 rule with 1 optimizing parameter. A lot of stuff get repeated and the book shouldn't be longer than 200 pages. There is a lot to learn if you are a novice trader and if you've never tried to develop a trading system. I think this book isn't worth half the selling price. Rather buy "The Encyclopedia of Trading Strategies (Hardcover)" by Jeffrey Owen Katz. You will learn something about GA and NN. Don't waste your time on this book. I'm selling mine.

41 of 49 people found the following review helpful:

1.0 out of 5 stars Useless, March 18, 2008

By	A.B. - See all my reviews

This book does not provide anything new about the current understanding of TA indicators. The properties and behaviors of the TA indicators under statistical studies are known long time ago. At the same time, this is not a book for anyone to study Monte Carlo, or Data mining. Simply put it: IT IS WORTHLESS.