AutoUpdate Foreign Exchange Trading System using Di?erential Evolution

Abstract

In this paper, we propose a real world application which is an automated foreign exchange trading system which update the trading rule automatically, using Differential Evolution( DE). There are many studies which have focused on trading system. In recent years, such studies have attracted attention because system can catch movement of market price accurately and quickly. DE is a simple yet powerful evolutionary algorithm for global numerical optimization. To verify the effectiveness of the method, we performed simulations using real historical trading data. DE was found to be superior compared to other previous methods in terms of precision and reliability.