Foreign exchange trading has emerged in recent times as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters, so that the creation of a system that effectively emulates the trading process will be very helpful. This chapter presents a novel trading system using Machine Learning methods of Genetic Algorithms and Reinforcement Learning. The system emulates trader behavior on the Foreign Exchange market and finds the most profitable trading strategy.
Foreign Exchange trading has emerged in recent times as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process will be very helpful. In this paper we try to create such a system using Machine learning approach to emulate trader behaviour on the Foreign Exchange market and to find the most profitable trading strategy.
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