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Type: Conference paper
Title: Enhancing profitability through interpretability in algorithmic trading with a multiobjective evolutionary fuzzy system
Author: Ghandar, A.
Michalewicz, Z.
Zurbrugg, R.
Citation: Proceedings of the 12th International Conference on Parallel Problem Solving from Nature, held in Taormina, Italy, 1-5 September, 2012 / C.A. Coello Coello, V. Cutello, K. Deb, S. Forrest, G. Nicosia and M. Pavone (eds.): pp.42-51
Publisher: Springer-Verlag
Publisher Place: Germany
Issue Date: 2012
Series/Report no.: Lecture Notes in Computer Science; 7492
ISBN: 9783642329630
ISSN: 0302-9743
Conference Name: International Conference on Parallel Problem Solving from Nature (12th : 2012 : Taormina, Italy)
Statement of
Adam Ghandar, Zbigniew Michalewicz and Ralf Zurbruegg
Abstract: This paper examines the interaction of decision model complexity and utility in a computational intelligence system for algorithmic trading. An empirical analysis is undertaken which makes use of recent developments in multiobjective evolutionary fuzzy systems (MOEFS) to produce and evaluate a Pareto set of rulebases that balance conflicting criteria. This results in strong evidence that controlling portfolio risk and return in this and other similar methodologies by selecting for interpretability is feasible. Furthermore, while investigating these properties we contribute to a growing body of evidence that stochastic systems based on natural computing techniques can deliver results that outperform the market.
Rights: © Springer-Verlag Berlin Heidelberg 2012
RMID: 0020122231
DOI: 10.1007/978-3-642-32964-7_5
Published version:
Appears in Collections:Computer Science publications

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