@techreport{neely:2001-009B,
	title = {Predicting Exchange Rate Volatility: Genetic
                 Programming vs. {GARCH} and Risk Metrics},
	address = {411 Locust Street, St. Louis, MO 63102-0442, USA},
	author = {Christopher J. Neely and Paul A. Weller},
	institution = {Economic, Research, Federal Reserve Bank of St.
                 Louis},
	month = {September},
	number = {2001-009B},
	type = {Working Paper},
	url = {http://research.stlouisfed.org/wp/2001/2001-009.pdf},
	year = {2001},
	biburl = {http://www.bibsonomy.org/bibtex/2f0e33fb1a50f51cd0cb55b2996db9ce0/brazovayeye},
	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},
	keywords = {algorithms, genetic programming }
}