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Trading the foreign exchange market with technical analysis and Bayesian statistics

Hassanniakalager, A., Sermpinis, G. and Stasinakis, C. (2021) Trading the foreign exchange market with technical analysis and Bayesian statistics. Journal of Empirical Finance, 63, pp. 230-251. (doi: 10.1016/j.jempfin.2021.07.006)

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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.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Stasinakis, Professor Charalampos and Hassanniakalager, Arman and Sermpinis, Professor Georgios
Creator Roles:
Hassanniakalager, A.Conceptualization, Methodology, Software, Visualization, Data curation, Writing – review and editing
Sermpinis, G.Writing – original draft, Investigation, Validation, Methodology
Stasinakis, C.Supervision, Software, Writing – review and editing, Data curation
Authors: Hassanniakalager, A., Sermpinis, G., and Stasinakis, C.
College/School:College of Social Sciences > Adam Smith Business School > Accounting and Finance
Journal Name:Journal of Empirical Finance
Publisher:Elsevier
ISSN:0927-5398
ISSN (Online):1879-1727
Published Online:19 July 2021
Copyright Holders:Copyright © 2021 Elsevier B.V.
First Published:First published in Journal of Empirical Finance 63: 230-251
Publisher Policy:Reproduced in accordance with the publisher copyright policy

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