Modelling and trading the Greek stock market with gene expression and genetic programing algorithms

Karathanasopoulos, A., Sermpinis, G. , Laws, J. and Dunis, C. (2014) Modelling and trading the Greek stock market with gene expression and genetic programing algorithms. Journal of Forecasting, 33(8), pp. 596-610. (doi: 10.1002/for.2290)

Abstract

This paper presents an application of the gene expression programming (GEP) and integrated genetic programming (GP) algorithms to the modelling of ASE 20 Greek index. GEP and GP are robust evolutionary algorithms that evolve computer programs in the form of mathematical expressions, decision trees or logical expressions. The results indicate that GEP and GP produce significant trading performance when applied to ASE 20 and outperform the well-known existing methods. The trading performance of the derived models is further enhanced by applying a leverage filter.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Laws, Mr Jason and Sermpinis, Professor Georgios
• Authors: Karathanasopoulos, A., Sermpinis, G., Laws, J., and Dunis, C.
• College/School: College of Social Sciences > Adam Smith Business School > Economics
• Journal Name: Journal of Forecasting
• Publisher: Wiley
• ISSN: 0277-6693
• ISSN (Online): 1099-131X
• Published Online: 25 September 2014
• Copyright Holders: Copyright © 2014 John Wiley and Sons, Ltd.
• First Published: First published in Journal of Forecasting 33(8):596-610
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher.