research-article

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

Authors:

Christopher D. ClackAuthors Info & Claims

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

Pages 1665 - 1672

https://doi.org/10.1145/1389095.1389407

Published: 12 July 2008 Publication History

Abstract

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.

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Cited By

Suzue KOfria CLalejini A(2025)Using Lineage Age to Augment Search Space Exploration in Lexicase SelectionGenetic Programming Theory and Practice XXI10.1007/978-981-96-0077-9_20(395-411)Online publication date: 28-Feb-2025
https://doi.org/10.1007/978-981-96-0077-9_20
Hornby GRothlauf F(2009)Steady-state ALPS for real-valued problemsProceedings of the 11th Annual conference on Genetic and evolutionary computation10.1145/1569901.1570011(795-802)Online publication date: 8-Jul-2009
https://dl.acm.org/doi/10.1145/1569901.1570011
Hornby G(2009)A Steady-State Version of the Age-Layered Population Structure EAGenetic Programming Theory and Practice VII10.1007/978-1-4419-1626-6_6(87-102)Online publication date: 20-Oct-2009
https://doi.org/10.1007/978-1-4419-1626-6_6
Show More Cited By

Index Terms

GP age-layer and crossover effects in bid-offer spread prediction
1. Computing methodologies
  1. Artificial intelligence

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cover image ACM Conferences

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

July 2008

1814 pages

ISBN:9781605581309

DOI:10.1145/1389095

Conference Chair:
Conor Ryan
University of Limerick, Ireland
,
Editor:
Maarten Keijzer
Chordiant Software International B.V., The Netherlands

Copyright © 2008 ACM.

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Published: 12 July 2008

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July 12 - 16, 2008

GA, Atlanta, USA

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Cited By

Suzue KOfria CLalejini A(2025)Using Lineage Age to Augment Search Space Exploration in Lexicase SelectionGenetic Programming Theory and Practice XXI10.1007/978-981-96-0077-9_20(395-411)Online publication date: 28-Feb-2025
https://doi.org/10.1007/978-981-96-0077-9_20
Hornby GRothlauf F(2009)Steady-state ALPS for real-valued problemsProceedings of the 11th Annual conference on Genetic and evolutionary computation10.1145/1569901.1570011(795-802)Online publication date: 8-Jul-2009
https://dl.acm.org/doi/10.1145/1569901.1570011
Hornby G(2009)A Steady-State Version of the Age-Layered Population Structure EAGenetic Programming Theory and Practice VII10.1007/978-1-4419-1626-6_6(87-102)Online publication date: 20-Oct-2009
https://doi.org/10.1007/978-1-4419-1626-6_6
O’Reilly UMcConaghy TRiolo R(2009)GPTP 2009: An Example of EvolvabilityGenetic Programming Theory and Practice VII10.1007/978-1-4419-1626-6_1(1-18)Online publication date: 20-Oct-2009
https://doi.org/10.1007/978-1-4419-1626-6_1

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