Evolving trading rule-based policies

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Title: Evolving trading rule-based policies
Authors: Bradley, Robert
Brabazon, Anthony
O'Neill, Michael
Permanent link: http://hdl.handle.net/10197/2739
Date: Apr-2010
Online since: 2011-01-21T14:59:07Z
Abstract: Trading-rule representation is an important factor to consider when designing a quantitative trading system. This study implements a trading strategy as a rule-based policy. The result is an intuitive human-readable format which allows for seamless integration of domain knowledge. The components of a policy are specified and represented as a set of rewrite rules in a context-free grammar. These rewrite rules define how the components can be legally assembled. Thus, strategies derived from the grammar are well-formed, domain-specific, solutions. A grammar-based Evolutionary Algorithm, Grammatical Evolution (GE), is then employed to automatically evolve intra-day trading strategies for the U.S. Stock Market. The GE methodology managed to discover profitable rules with realistic transaction costs included. The paper concludes with a number of suggestions for future work.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: Springer
Journal: Proceedings of EvoFIn 2010, Applications of Evolutionary Computation, Lecture Notes in Computer Science
Copyright (published version): 2010 Verlag Berlin Heidelberg
Keywords: Trading-ruleGrammatical evolutionTrading systems
Subject LCSH: Evolutionary computation
DOI: 10.1007/978-3-642-12242-2_26
Other versions: http://dx.doi.org/10.1007/978-3-642-12242-2_26
Language: en
Status of Item: Peer reviewed
Is part of: Di Chio, C. ...et al (ed.s). Applications of Evolutionary Computation EvoApplications 2010: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoMUSART, and EvoTRANSLOG, Istanbul, Turkey, April 7-9, 2010, Proceedings, Part II
Conference Details: EvoFIN 4th European Event on Evolutionary and Natural Computation in Finance and Economics, at EvoStar 2010, Istanbul, 7-9 April 2010
ISBN: 978-3-642-12241-5
Appears in Collections:FMC² Research Collection
Computer Science Research Collection
Business Research Collection

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