Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals by David R. Aronson

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Description

It is written by David R. Aronson, “Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals,” expounds on the scientific method of analytics and how to apply it when observing trading charts and systems. Highly credited as a book that any novice trader should read, “Evidence-Based Technical Analysis” gives readers an edge in the market to avoid many costly paths, albeit many would claim that the information within the pages may not necessarily lead its reader to a more profitable path. “Evidence-Based Technical Analysis” is a highly-advanced dispenser of knowledge that delves into this evidence-based methodology through comprehensive coverage. With this current method, David Aronson reveals how this method is specifically designed for evaluating the performance of rules/signals that are discovered by data mining.

About the Author

David Aronson is an adjunct professor of finance at Baruch College’s Zicklin School of Bussiness in New York, where he teaches a graduate-level course in technical analysis to MBA and financial-engineering students, and vice-president of Hood River Research Inc., a firm that develops signal filters and predictive models. He was formerly a proprietary trader and president of Raden Research Group Inc., a consulting firm that developed the data-mining software PRISM and filters and systems for various trading firms. Prior to that, he founded AdvoCom Corporation, which managed client funds in portfolios of futures trading advisors using portfolio optimization. He received a BA in philosophy from Layfette College in 1967 and served in the Peace Corps in El Salvador.

Table of Contents

  • Acknowledgements
  • About the Author
  • Introduction
    • 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 of Study of Rule Data Mining for the S&P 500
      • Chapter 9: Case Study Results and the Future of TA
  • Appendix: Proof That Detrending Based on Position Bias
  • Index