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

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@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