Usage patterns of trading rules in stock market trading strategies optimized with evolutionary methods

Authors:
Krzysztof Michalak;Patryk Filipiak;Piotr Lipinski
Affiliations:
Institute of Business Informatics, Wroclaw University of Economics, Wroclaw, Poland;Institute of Computer Science, University of Wroclaw, Wroclaw, Poland;Institute of Computer Science, University of Wroclaw, Wroclaw, Poland
Venue:
EvoApplications'13 Proceedings of the 16th European conference on Applications of Evolutionary Computation
Year:
2013

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Abstract

This paper proposes an approach to analysis of usage patterns of trading rules in stock market trading strategies. Analyzed strategies generate trading decisions based on signals produced by trading rules. Weighted sets of trading rules are used with parameters optimized using evolutionary algorithms. A novel approach to trading rule pattern discovery, inspired by association rule mining methods, is proposed. In the experiments, patterns consisting of up to 5 trading rules were discovered which appear in no less than 50% of trading experts optimized by evolutonary algorithm.