Predicting exchange rate volatility: genetic programming vs. GARCH and RiskMetrics

Christopher Neely and Paul A. Weller

No 2001-009, Working Papers from Federal Reserve Bank of St. Louis

Abstract: This article investigates the use of genetic programming to forecast out-of-sample daily volatility in the foreign exchange market. Forecasting performance is evaluated relative to GARCH(1,1) and RiskMetrics models for two currencies, DEM and JPY. Although the GARCH/RiskMetrics models appear to have a inconsistent marginal edge over the genetic program using the mean-squared-error (MSE) and R2 criteria, the genetic program consistently produces lower mean absolute forecast errors (MAE) at all horizons and for both currencies.

Keywords: Foreign exchange rates; Forecasting; Programming (Mathematics) (search for similar items in EconPapers)
Date: 2001
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Citations: View citations in EconPapers (4)

Published in Federal Reserve Bank of St. Louis Review, May/June 2002, 84(3), pp. 43-54

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Persistent link: https://EconPapers.repec.org/RePEc:fip:fedlwp:2001-009

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DOI: 10.20955/wp.2001.009

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