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

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

Description

Evidenced-Based technical Analysis emphasizes the function of the scientific method along with created and enhanced statistical examinations to find out the effectiveness of technical trading signals. David Aronson renders his expertise in revealing the reliability of the signals brought forth from data mining. Aronson covers this whole complex study that yields significant findings he generously shares in this reading.

This material is rich in technical information as well as practical advice to traders who dare to go beyond the rudiments of trading. Unleash the power of technical analysis into your trading methodology and open doors of endless possibilities of profitable trading. Evidenced-Based Technical Analysis will guide you every step of the way to a rich technical approach to trading. 

About the Author

David Aronson is a professor of Finance at the Zicklin School of Business. He started studying technical analysis since he was a teenager and worked as a broker for Merrill Lynch in 1973. After several years, Aronson conducted an independent study of the nascent field of managed futures strategies. 

Aronson founded Raden Research Group in 1982 and studied about data mining. He published several articles and dedicated his time in developing theories and significant findings by releasing journals. 

Table of Contents

Evidenced-Based technical Analysis contains nine comprehensive chapters covering the following topics:

Acknowledgments

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 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

Notes 

Index