Working Paper

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

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);

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

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Bibliographic Information

Provider: Federal Reserve Bank of St. Louis

Part of Series: Working Papers

Publication Date: 2001

Number: 2001-009