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.

在本研究中，研究了技术分析和贝叶斯统计在交易 EUR/USD、GBP/USD 和 USD/JPY 汇率时的盈利能力。为此，生成了 7846 条技术规则，并通过数据窥探程序评估其盈利能力。然后，最有希望的规则与朴素贝叶斯、相关向量机、动态模型平均、动态模型选择和贝叶斯正则化神经网络模型相结合。研究结果表明，技术分析在外汇交易中具有价值，但利润空间很小。另一方面，贝叶斯统计似乎将技术规则的盈利能力提高了五倍。