Trading the foreign exchange market with technical analysis and Bayesian Statistics

Arman Hassanniakalager, Georgios Sermpinis and Charalampos Stasinakis

Journal of Empirical Finance, 2021, vol. 63, issue C, 230-251

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 data snooping procedure. Then, the most promising rules are combined with a Naïve Bayes, a Relevance Vector Machine, a Dynamic Model Averaging, a Dynamic Model Selection and a Bayesian regularized Neural Network model. The findings show that 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 five times.

Keywords: Trading; Technical analysis; Foreign exchange; Bayesian averaging; Relevance Vector Machines (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:63:y:2021:i:c:p:230-251

DOI: 10.1016/j.jempfin.2021.07.006

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