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Erschienen in:
2002 | OriginalPaper | Buchkapitel
Using a Genetic Program to Predict Exchange Rate Volatility
verfasst von : Christopher J. Neely, Paul A. Weller
Erschienen in: Genetic Algorithms and Genetic Programming in Computational Finance
Verlag: Springer US
Enthalten in: Professional Book Archive
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This article illustrates the strengths and weaknesses of genetic programming in the context of forecasting out-of-sample volatility in the DEM/USD and JPY/USD markets. GARCH(1,1) models serve used as a benchmark. While the GARCH model outperforms the genetic program at short horizons using the mean-squared-error (MSE) criterion, the genetic program often outperforms the GARCH at longer horizons and consistently returns lower mean absolute forecast errors (MAE).