Abstract
This paper employs genetic programming to discover statistical arbitrage strategies on the banking sector in the Euro Stoxx universe. Binary decision rules are evolved using two different representations. The first is the classical single tree approach, while the second is a dual tree structure where evaluation is contingent on the current market position. Hence, buy and sell rules are co-evolved. Both methods are capable of discovering significant statistical arbitrage strategies. © 2008 Springer-Verlag Berlin Heidelberg.
Cite
CITATION STYLE
Saks, P., & Maringer, D. (2008). Genetic programming in statistical arbitrage. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4974 LNCS, pp. 73–82). https://doi.org/10.1007/978-3-540-78761-7_8
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