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More About This Title Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals
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.