Optimization of the trading rule in foreign exchange using genetic algorithm

The generation of profitable trading rules for Foreign Exchange (FX) investments is a difficult but popular problem. The use of Machine Learning in this problem allows us to obtain objective results by using information of the past market behavior. In this paper, we propose a Genetic Algorithm (GA) system to automatically generate trading rules based on Technical Indexes. Unlike related researches in the area, our work focuses on calculating the most appropriate trade timing, instead of predicting the trading prices. Categories and Subject Descriptors I.2.8 [Artificial Intelligence]: Problem Solving, Control Methods, and Search - Heuristic methods. J.4 [Social and behavioral sciences]: Economics. General Terms: Algorithms, Economics. Keywords Genetic Algorithms (GA), Optimization, Finance, Foreign Exchange (FX), Technical Analysis.

• Type: Conference
• Year: 2009
• Where: GECCO
• Authors: Akinori Hirabayashi, Claus de Castro Aranha, Hitoshi Iba
• Keywords: Artificial Intelligence, Foreign Exchange, GECCO 2009, Genetic Algorithms, Trading Rules