Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals / Edition 1by David Aronson
Pub. Date: 11/03/2006
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/i>
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.
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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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
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.