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Karathanasopoulos, Andreas; Sermpinis, Georgios; Laws, Jason; Dunis, Christian (2014)
Publisher: Wiley
Languages: English
Types: Article
Subjects:
Identifiers:doi:10.1002/for.2290
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.
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    • Kwon, Y., and Moon, B. (2003), 'Daily Stock Prediction Using Neuro-genetic Hybrids', Genetic and Evolutionary Computation, 2203- 2214.
    • Zargari S.A., Zabihi S., Alavi A.H., Gandomi A.H., (2012), 'A Computational Intelligence Based Approach for Short-Term Traffic Flow Prediction', Expert Systems, 29, 2, 124-142.
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