Modelling and Trading the Greek Stock Market with Gene Expression and Genetic Programing Algorithms

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. Copyright © 2014 John Wiley & Sons, Ltd.     

Business cycle analysis and forecasting with a structural vector auto regression model for wales

Recent innovations in the Welsh economy have led to the view that the region's economy is likely to exhibit differential responses to financial and external shocks compared to the rest of the UK. This is examined with the aid of a structural VAR forecasting model for Wales.