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GECCO
2008
Springer

GP age-layer and crossover effects in bid-offer spread prediction

14 years 19 days ago
GP age-layer and crossover effects in bid-offer spread prediction
The bid-offer spread on equity options is a key source of profits for market makers, and a key cost for those trading in the options. Spreads are influenced by dynamic market factors, but is there also a predictable element and can Genetic Programming be used for such prediction? We investigate a standard GP approach and two optimisations — age-layering and a novel crossover operator. If both are beneficial as independent optimisations, will they be mutually beneficial when applied simultaneously? Our experiments show a degree of success in predicting spreads, we demonstrate significant benefits for each optimisation technique used individually, and we show that when both are used together significant detrimental over-fitting can occur. Categories and Subject Descriptors I.2.M [Artificial Intelligence]: Miscellaneous General Terms Algorithms, Experimentation Keywords GP, Finance, Options, Spreads, Age Layers, ALPS, Crossover
Amy Willis, Suneer Patel, Christopher D. Clack
Added 09 Nov 2010
Updated 09 Nov 2010
Type Conference
Year 2008
Where GECCO
Authors Amy Willis, Suneer Patel, Christopher D. Clack
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