Book Description
EvidenceBased 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
 Cover
 Contents
 Title
 Copyright
 Dedication
 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
 Subjective TA is Not Legitimate Knowledge
 A Personal Anecdote: First A True TA Believer, Then A Skeptic
 The Mind: A Natural Pattern Finder
 The Epidemic of Weird Beliefs
 Cognitive Psychology: Heuristics, Biases, and Illusions
 Human Information Processing Limitations
 Too Dang Certain: The Overconfidence BIAS
 SecondHand Information BIAS: The Power of A Good Story
 Confirmation BIAS: How Existing Beliefs Filter Experience and Survive Contradicting Evidence
 Illusory Correlations
 Misplaced Faith in Chart Analysis
 The Intuitive Judgment and The Role of Heuristics
 The Representativeness Heuristic and The Illusion Trends and Patterns in Charts: Real and Fake
 The Antidote To Illusory Knowledge: The Scientific Method

Chapter 3: The Scientific Method and Technical Analysis
 The Most Important Knowledge of All: A Method to Get More
 The Legacy of Greek Science: A Mixed Blessing
 The Birth of The Scientific Revolution
 Faith in Objective Reality and Objective Observations
 The Nature of Scientific Knowledge
 The Role of Logic In Science
 The Philosophy of Science
 The End Result: The HypotheticoDeductive Method
 Rigorous and Critical Analysis of Observed Results
 Summary of Key Aspects of The Scientific Method
 If TA Were to Adopt The Scientific Method
 Objectification of Subjective TA: An Example
 Subsets of TA

Chapter 4: Statistical Analysis
 A Preview of Statistical Reasoning
 The Need for Rigorous Statistical Analysis
 An Example of Sampling and Statistical Inference
 Probability Experiments and Random Variables
 Statistical Theory
 Descriptive Statistics
 Probability
 Probability Distributions of Random Variables
 Relationship Between Probability and Fractional Area of The Probability Distribution
 The Sampling Distribution: The Most Important Concept in Statistical Inference
 Deriving The Sampling Distribution: The Classical Approach
 Deriving The Sampling Distribution With The ComputerIntensive Approach
 Preview of Next Chapter
 Chapter 5: Hypothesis Tests and Confidence Intervals

Chapter 6: DataMining Bias: The Fool’s Gold of Objective TA
 Falling into The PIT: Tales of The DataMining BIAS
 The Problem of Erroneous Knowledge in Objective Technical Analysis
 Data Mining
 Objective TA Research
 Data Mining and Statistical Inference
 DataMining BIAS: An Effect With Two Causes
 Experimental Investigation of The DataMining BIAS
 Solutions: Dealing With The DataMining BIAS
 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
 Data Mining BIAS and Rule Evaluation
 Avoidance of Data Snooping BIAS
 Analyzed Data Series
 Technical Analysis Themes
 Performance Statistic: Average Return
 No Complex Rules Were Evaluated
 The Case Study Defined in Statistical Terms
 Rules: Transforming Data Series Into Market Positions
 TimeSeries Operators
 Input Series To Rules: Raw Time Series and Indicators
 Table of 40 Input Series Used in Case Study
 The Rules
 Chapter 9: Case Study Results and the Future of TA

Chapter 8: Case Study of Rule Data Mining for the S&P 500
 Appendix: Proof That Detrending Is Equivalent to Benchmarking Based on Position Bias
 Index
Product Information
 Title: EvidenceBased Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals
 Author(s):
 Release date: November 2006
 Publisher(s): Wiley
 ISBN: 9780470008744