Trading the Foreign Exchange Market with Technical Analysis and Bayesian Statistics

Abstract

In this study, the profitability of technical analysis and Bayesian Statistics in trading the EUR/USD, GBP/USD, and USD/JPY exchange rates are examined. For this purpose, seven thousand eight hundred forty-six technical rules are generated and their profitability is assessed through a novel data snooping procedure. Then, the most promising rules are combined with a Naïve Bayes, a Relevance Vector Machines, Bayesian Model Averaging, a Bayesian Model Selection and a Bayesian regularised Neural Network model. In terms of our results, technical analysis has value in foreign exchange trading but the profit margins are small. On the other hand, Bayesian Statistics seems to increase the profitability of technical rules up to four times.

Keywords: Trading, Technical Analysis, Foreign Exchange, Bayesian Averaging, Relevance Vector Machines

JEL Classification: C11, C12, C53