The syntax of stock selection: grammatical evolution of a stock picking model

Mcgee, Richard, O'Neill, Michael and Brabazon, Anthony (2010) The syntax of stock selection: grammatical evolution of a stock picking model. Evolutionary Computation (CEC), 2010 IEEE Congress on, Barcelona, Spain. 18 - 23 Jul 2010. pp. 1-8 . (doi:10.1109/CEC.2010.5586001).

Abstract

A significant problem in the area of stock selection is that of identifying the factors that affect a security's return. While modern portfolio theory suggests a linear multi-factor model in the form of Arbitrage Pricing Theory it does not suggest the identity, or even the number, of risk factors in the model. Candidate factors for inclusion in a fundamental model can include hundreds of data points for each firm and with thousands of firms in the fund manager's selection universe the model specification problem encompasses a large, computationally intense search space. Grammatical Evolution (GE) is a form of evolutionary computing that has been used successfully in model induction problems involving large search spaces. GE is applied to evolve a stock selection model with a customized mapping process developed specifically to enhance the performance of evolutionary operators for this problem. Stock selection models are rated using fitness functions commonly employed in asset management; the information coefficient and the inter-quantile return spread. The findings of the paper indicate that evolutionary computing is an excellent tool for the development of stock picking models

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