Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals / Edition 1

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"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

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Editorial Reviews

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

  • ISBN-13: 9780470008744
  • Publisher: Wiley
  • Publication date: 11/3/2006
  • Series: Wiley Trading Series , #274
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 544
  • Sales rank: 704,712
  • Product dimensions: 6.46 (w) x 9.09 (h) x 1.66 (d)

Meet the Author

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.

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Table of Contents


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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Customer Reviews

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Sort by: Showing all of 2 Customer Reviews
  • Anonymous

    Posted August 15, 2013

    Great book but why do i have to always pay more for eBooks on No

    Great book but why do i have to always pay more for eBooks on Nook than I do on Kindle? I think is time to trash the nook as kindle is $2.49 cheaper

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  • Anonymous

    Posted November 20, 2006


    David Aronson persuasively presents his case - the scientific method and proper statistical evaluations must be applied to technical analysis in order to assure its relevance. Most technical indicators and concepts are subjective and untrustworthy as they lack predictive power. Objective technical methods are better because they can be tested to see if they contain the legitimate knowledge and predictive power we seek. But evidence-based technical analysis (EBTA) goes further. Reports of profitable back tested results are not enough because testing which has not taken into account data mining biases or that shades statistical methods can produce deceptive or mediocre results. The value of this book will be reinforced by the future research of supporters of EBTA. Critics of EBTA will declare that technical analysis is more art than science. Aronson exposes the weakness of that claim by showing how statistical methods can be applied to commonly used technical indicators, taking into account the data-mining biases he so well describes, to seek trading signals with statistically significant returns. He shares his results in Part II of the book. This book is well-written and organized. Aronson¿s lifetime pursuit of intellectual honesty is evident, and his Wall Street experience is solid. Numerous footnotes stimulate further study.

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