Sermpinis, G., Laws, J., Karathanasopoulos, A., and Dunis, C.L. (2012) Forecasting and trading the EUR/USD exchange rate with Gene Expression and Psi Sigma Neural Networks. Expert Systems with Applications, 39 (10). pp. 8865-8877. (doi:10.1016/j.eswa.2012.02.022)
Full text not currently available from Enlighten.
The motivation for this paper is to investigate the use of two promising classes of artificial intelligence models, the PsiSigmaNeuralNetwork (PSI) and the GeneExpression algorithm (GEP), when applied to the task of forecasting and trading the EUR/USDexchangerate. This is done by benchmarking their results with a Multi-Layer Perceptron (MLP), a Recurrent NeuralNetwork (RNN), a genetic programming algorithm (GP), an autoregressive moving average model (ARMA) plus a naïve strategy. We also examine if the introduction of a time-varying leverage strategy can improve the trading performance of our models.
|Glasgow Author(s) Enlighten ID:||Sermpinis, Dr Georgios|
|Authors:||Sermpinis, G., Laws, J., Karathanasopoulos, A., and Dunis, C.L.|
|College/School:||College of Social Sciences > Adam Smith Business School > Economics|
|Journal Name:||Expert Systems with Applications|
|Published Online:||22 February 2012|