Predicting Exchange Rate Volatility: Genetic Programming vs. GARCH and Risk Metrics

Created by W.Langdon from gp-bibliography.bib Revision:1.8081

@TechReport{neely:2001-009B,

• author = "Christopher J. Neely and Paul A. Weller",
• title = "Predicting Exchange Rate Volatility: Genetic Programming vs. GARCH and Risk Metrics",
• institution = "Economic, Research, Federal Reserve Bank of St. Louis",
• year = "2001",
• type = "Working Paper",
• number = "2001-009B",
• address = "411 Locust Street, St. Louis, MO 63102-0442, USA",
• month = sep,
• keywords = "genetic algorithms, genetic programming",
• URL = "http://research.stlouisfed.org/wp/2001/2001-009.pdf",
• 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.",
• size = "30 pages",

}

Genetic Programming entries for Christopher J Neely Paul A Weller

Citations