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.
Status: Published in Federal Reserve Bank of St. Louis Review, May/June 2002, 84(3), pp. 43-54
File(s): File format is application/pdf http://research.stlouisfed.org/wp/more/2001-009
Provider: Federal Reserve Bank of St. Louis
Part of Series: Working Papers
Publication Date: 2001