Genetic multi-model composite forecast for non-linear prediction of exchange rates

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@Article{Alvarez-Diaz:2005:EE,

• author = "Marcos Alvarez-Diaz and Alberto Alvarez",
• title = "Genetic multi-model composite forecast for non-linear prediction of exchange rates",
• journal = "Empirical Economics",
• year = "2005",
• volume = "30",
• number = "3",
• pages = "643--663",
• month = oct,
• keywords = "genetic algorithms, genetic programming, Composite-forecast or data-fusion, neural networks, ANN, exchange-rate forecasting",
• ISSN = "0377-7332",
• DOI = "doi:10.1007/s00181-005-0249-5",
• size = "21 pages",
• abstract = "The existence of non-linear deterministic structures in the dynamics of exchange rates has already been amply demonstrated. In this paper, we attempt to exploit these non-linear structures employing forecasting techniques, such as Genetic Programming and Neural Networks, in the specific case of the Yen/US$ and Pound Sterling/US$ exchange rates. Forecasts obtained from genetic programming and neural networks are then genetically fused to verify whether synergy provides an improvement in the predictions. Our analysis considers both point predictions and the anticipating of either depreciations or appreciations.",

}

Genetic Programming entries for Marcos Alvarez-Diaz Alberto Alvarez Diaz

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