PREDICCIÓN NO-LINEAL DE TIPOS DE CAMBIO: ALGORITMOS GENÉTICOS, REDES NEURONALES Y FUSIÓN DE DATOS

Marcos Álvarez-Díaz and Alberto Álvarez

No 301, Working Papers from Universidade de Vigo, Departamento de Economía Aplicada

Abstract: It is widely proved the existence of non-linear deterministic structures in the exchange rates dynamic. In this work we intend to exploit these non-linear structures using forecasting methods such as Genetic Algorithm and Neural Networks in the specific case of the Yen/$ and British Pound/$ exchange rates. We also employ a novel perspective, called Data Fusion, based on the combination of the obtained results by the non-linear methods to verify if it exists a synergic effect which permits a predictive improvement. The analysis is performed considering both the point prediction and the devaluation or appreciation anticipation.

Keywords: Data Fusion; Genetic Algorithms; Neural Networks; Exchange Rates Forecasting (search for similar items in EconPapers)
JEL-codes: C14 C53 G14 (search for similar items in EconPapers)
Pages: 38 pages
Date: 2003-02
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Persistent link: https://EconPapers.repec.org/RePEc:vig:wpaper:0301

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