Investigating the effect of different GP algorithms on the non-stationary behavior of financial markets

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Kampouridis:2011:CIFEr,

• author = "Michael Kampouridis and Shu-Heng Chen and Edward Tsang",
• title = "Investigating the effect of different GP algorithms on the non-stationary behavior of financial markets",
• booktitle = "IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr 2011)",
• year = "2011",
• month = "11-15 " # apr,
• address = "Paris",
• size = "8 pages",
• abstract = "This paper extends a previous market microstructure model, where we used Genetic Programming (GP) as an inference engine for trading rules, and Self Organising Maps as a clustering machine for those rules. Experiments in that work took place under a single financial market and investigated whether its behaviour is non-stationary or cyclic. Results showed that the market's behaviour was constantly changing and strategies that would not adapt to these changes, would become obsolete, and their performance would thus decrease over time. However, because experiments in that work were based on a specific GP algorithm, we are interested in this paper to prove that those results are independent of the choice of such algorithms. We thus repeat our previous tests under two more GP frameworks. In addition, while our previous work surveyed only a single market, in this paper we run tests under 10 markets, for generalisation purposes. Finally, we deepen our analysis and investigate whether the performance of strategies, which have not co-evolved with the market, follows a continuous decrease, as it has been previously suggested in the agent-based artificial stock market literature. Results show that our previous results are not sensitive to the choice of GP. Strategies that do not co-evolve with the market, become ineffective. However, we do not find evidence for a continuous performance decrease of these strategies.",
• keywords = "genetic algorithms, genetic programming, agent-based artificial stock market literature, financial markets, genetic programming algorithm, market microstructure model, nonstationary behaviour, self organising maps, financial data processing, marketing data processing, multi-agent systems, self-organising feature maps, stock markets",
• DOI = "doi:10.1109/CIFER.2011.5953568",
• ISSN = "pending",
• notes = "Also known as \cite{5953568}",

}

Genetic Programming entries for Michael Kampouridis Shu-Heng Chen Edward P K Tsang

Citations