Evidence-Based Technical Analysis
Applying the Scientific Method and Statistical Inference to Trading Signals
Published on 11. July 2011
544 pages
978-1-118-16058-9 (ISBN)
Description
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.
More details
Other editions
Additional editions
Software
12/2011
Wiley
€116.38
Shipment within 15-20 days
David Aronson
Evidence-Based Technical Analysis
Applying the Scientific Method and Statistical Inference to Trading Signals
Book
12/2006
Wiley
€101.50
Shipment within 10-20 days
Person
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.
Content
Acknowledgments.
About the Author.
Introduction.
PART I Methodological, Psychological, Philosophical, andStatistical Foundations.
CHAPTER 1 Objective Rules and Their Evaluation.
CHAPTER 2 The Illusory Validity of Subjective TechnicalAnalysis.
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 ObjectiveTA.
CHAPTER 7 Theories of Nonrandom Price Motion.
PART II Case Study: Signal Rules for the S&P 500Index.
CHAPTER 8 Case Study of Rule Data Mining for the S&P500.
CHAPTER 9 Case Study Results and the Future of TA.
APPENDIX Proof That Detrending Is Equivalent to BenchmarkingBased on Position Bias.
Notes.
Index.
About the Author.
Introduction.
PART I Methodological, Psychological, Philosophical, andStatistical Foundations.
CHAPTER 1 Objective Rules and Their Evaluation.
CHAPTER 2 The Illusory Validity of Subjective TechnicalAnalysis.
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 ObjectiveTA.
CHAPTER 7 Theories of Nonrandom Price Motion.
PART II Case Study: Signal Rules for the S&P 500Index.
CHAPTER 8 Case Study of Rule Data Mining for the S&P500.
CHAPTER 9 Case Study Results and the Future of TA.
APPENDIX Proof That Detrending Is Equivalent to BenchmarkingBased on Position Bias.
Notes.
Index.
