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

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Introduction

Technical analysis (TA) is the study of recurring patterns in financial market data with the intent of forecasting future price movements.1 It is comprised of numerous analysis methods, patterns, signals, indicators, and trading strategies, each with its own cheerleaders claiming that their approach works.

Much of popular or traditional TA stands where medicine stood before it evolved from a faith-based folk art into a practice based on science. Its claims are supported by colorful narratives and carefully chosen (cherry picked) anecdotes rather than objective statistical evidence.

This book’s central contention is that TA must evolve into a rigorous observational science if it is to deliver on its claims and remain relevant. The scientific method is the only rational way to extract useful knowledge from market data and the only rational approach for determining which TA methods have predictive power. I call this evidence-based technical analysis (EBTA). Grounded in objective observation and statistical inference (i.e., the scientific method), EBTA charts a course between the magical thinking and gullibility of a true believer and the relentless doubt of a random walker.

Approaching TA, or any discipline for that matter, in a scientific manner is not easy. Scientific conclusions frequently conflict with what seems intuitively obvious. To early humans it seemed obvious that the sun circled the earth. It took science to demonstrate that this intuition was wrong. An ...

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