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Evolving Market Index Trading Rules using
Grammatical Evolution
Michael O'Neill 2 , Anthony Brabazon 1 , Conor Ryan 2 , and J.J. Collins 2
1 Dept. Of Accountancy, University College Dublin, Ireland.
Anthony.Brabazon@ucd.ie
2 Dept. Of Computer Science And Information Systems,
University of Limerick, Ireland.
fMichael.ONeilljConor.RyanjJ.J.Collinsg@ul.ie

Abstract. This study examines the potential of an evolutionary auto- matic programming methodology to uncover a series of useful technical trading rules for the UK FTSE 100 stock index. Index values for the pe- riod 26/4/1984 to 4/12/1997 are used to train and test the model. The preliminary ndings indicate that the methodology has much potential, outperforming the benchmark strategy adopted.
1 Introduction The objective of this study is to determine whether an evolutionary automatic programming methodology, Grammatical Evolution, is capable of uncovering useful technical trading rules for the UK FTSE 100 index. The paper is organised as follows. Section two discusses the background to the technical indicators utilised in this study. Section three describes the evolution- ary algorithm adopted, Grammatical Evolution [16] [18]. Section four outlines the data and function sets used. The following sections provide the results of the study followed by a discussion of these results and nally a number of conclusions are derived. 1.1 Technical analysis A market index is comprised of a weighted average measure of the price of individual shares which make up that market. The value of the index represents an aggregation of the balance of supply and demand for these shares. Some market traders, known as technical analysts, believe that prices move in trends and that price patterns repeat themselves [14]. If we accept this premise, that there are rules, although not necessarily static rules, underlying price behaviour it follows that trading decisions could be enhanced through use of an appropri- ate rule induction methodology ...

@inproceedings{oneill01evolvingMarket,
  author={Michael O'Neill and Anthony Brabazon and Conor Ryan and J. J. Collins},
  title={Evolving Market Index Trading Rules Using Grammatical Evolution},
  year={2001},
  pages={343-352},
  booktitle={EvoWorkshops 2001},
  url={http://www.isrl.uiuc.edu/~amag/langev/paper/oneill01evolvingMarket.html}
}

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