Forecasting and trading the EUR/USD exchange rate with Gene Expression and Psi Sigma Neural Networks

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@Article{Sermpinis20128865,

• author = "Georgios Sermpinis and Jason Laws and Andreas Karathanasopoulos and Christian L. Dunis",
• title = "Forecasting and trading the {EUR/USD} exchange rate with Gene Expression and Psi Sigma Neural Networks",
• journal = "Expert Systems with Applications",
• volume = "39",
• number = "10",
• pages = "8865--8877",
• year = "2012",
• ISSN = "0957-4174",
• DOI = "doi:10.1016/j.eswa.2012.02.022",
• URL = "http://www.sciencedirect.com/science/article/pii/S0957417412002667",
• keywords = "genetic algorithms, genetic programming, Genetic Expression, Psi Sigma Networks, Recurrent networks, Multi-Layer Perceptron networks, Quantitative trading strategies",
• abstract = "The motivation for this paper is to investigate the use of two promising classes of artificial intelligence models, the Psi Sigma Neural Network (PSI) and the Gene Expression algorithm (GEP), when applied to the task of forecasting and trading the EUR/USD exchange rate. This is done by benchmarking their results with a Multi-Layer Perceptron (MLP), a Recurrent Neural Network (RNN), a genetic programming algorithm (GP), an autoregressive moving average model (ARMA) plus a naive strategy. We also examine if the introduction of a time-varying leverage strategy can improve the trading performance of our models.",

}

Genetic Programming entries for Georgios Sermpinis Jason Laws Andreas S Karathanasopoulos Christian L Dunis

Citations