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



"In clear language, Aronson demonstrates the theoretical flaws in interpretative technical analysis methodologies, the flawed premises and conclusions of the Efficient Market Hypothesis, and the appropriate techniques for developing and testing technical analysis methods that do have validity. Readers will learn a lot from this book."
Jack Schwager, author of Market Wizards and the Schwager on Futures book series

"Aronson's explanation of data mining is a must-read for every analyst, and his overall discussion of statistical inference is critical to success. The book is filled with commonsense examples and provides a testing and validation process that saves time, frustration, and money."
Perry Kaufman, author of New Trading Systems and Methods, Fourth Edition

"This book debunks many of the myths of technical analysis. One should read this book before buying a technical system. The book is a good reference to the literature on the subject with extensive footnotes and bibliography."
Sandor Straus, Managing Member, Merfin, LLC

"You may not agree with everything David Aronson says in this controversial, but compelling new study. Still, every trader who wants to invest technical analysis with the dignity of a great science should read this discerning account."
Nelson Freeburg, Editor, Formula Research

"There are illusions of the mind that are every bit as real as optical illusions. Aronson's criticisms of popular forms of technical analysis are right on target."
Fred Gehm, author of Quantitative Trading and Money Management

DAVID ARONSON is an adjunct professor at Baruch College, where he teaches a graduate- level course in technical analysis. He is also a Chartered Market Technician and has published articles on technical analysis. Previously, Aronson was a proprietary trader and technical analyst for Spear Leeds & Kellogg. He founded Raden Research Group, a firm that was an early adopter of data mining within financial markets. Prior to that, Aronson founded AdvoCom, a firm that specialized in the evaluation of commodity money managers and hedge funds, their performance, and trading methods. For free access to the algorithm for testing data mined rules, go to www.evidencebasedta.com.


About the Author.


PART I Methodological, Psychological, Philosophical, and Statistical Foundations.

CHAPTER 1 Objective Rules and Their Evaluation.

CHAPTER 2 The Illusory Validity of Subjective Technical Analysis.

CHAPTER 3 The Scientific Method and Technical Analysis.

CHAPTER 4 Statistical Analysis.

CHAPTER 5 Hypothesis Tests and Confidence Intervals.

CHAPTER 6 Data-Mining Bias: The Fool’s Gold of Objective TA.

CHAPTER 7 Theories of Nonrandom Price Motion.

PART II Case Study: Signal Rules for the S&P 500 Index.

CHAPTER 8 Case Study of Rule Data Mining for the S&P 500.

CHAPTER 9 Case Study Results and the Future of TA.

APPENDIX Proof That Detrending Is Equivalent to Benchmarking Based on Position Bias.



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