Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
Evolution Strategy in Portfolio Optimization
Selected Papers from the 5th European Conference on Artificial Evolution
Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series)
Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series)
Dependency mining in large sets of stock market trading rules
Enhanced methods in computer security, biometric and artificial intelligence systems
ECGA vs. BOA in discovering stock market trading experts
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Euro-Par 2010 Proceedings of the 2010 conference on Parallel processing
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This paper proposes a decision support system for stock market trading, which is based on an evolution strategy algorithm applied to construct an efficient stock market trading expert built as a weighted average of a number of specific stock market trading rules analysing financial time series of recent price quotations. Although applying separately, such trading rules, which come from practictioner knowledge of financial analysts and market investors, give average results, combining them into one trading expert leads to a significant improvement and efficient investment strategies. Experiments on real data from the Paris Stock Exchange confirm the financial relevance of investment strategies based on such trading experts.