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

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Author Info

  • Christopher J. Neely
  • Paul A. Weller

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.

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Bibliographic Info

Paper provided by Federal Reserve Bank of St. Louis in its series Working Papers with number 2001-009.

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Date of creation: 2001
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Publication status: Published in Federal Reserve Bank of St. Louis Review, May/June 2002, 84(3), pp. 43-54
Handle: RePEc:fip:fedlwp:2001-009

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Keywords: Foreign exchange rates ; Forecasting ; Programming (Mathematics);

References

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  1. Baillie, Richard T & Bollerslev, Tim, 1991. "Intra-day and Inter-market Volatility in Foreign Exchange Rates," Review of Economic Studies, Wiley Blackwell, vol. 58(3), pages 565-85, May.
  2. West, K.D. & Cho, D., 1993. "The Predictive Ability of Several Models of Exchange Rate Volatility," Working papers 9317r, Wisconsin Madison - Social Systems.
  3. Christopher J. Neely & Paul A. Weller & Robert Dittmar, 1997. "Is technical analysis in the foreign exchange market profitable? a genetic programming approach," Working Papers 1996-006, Federal Reserve Bank of St. Louis.
  4. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
  5. Christopher J. Neely, 1998. "Target zones and conditional volatility: the role of realignments," Working Papers 1994-008, Federal Reserve Bank of St. Louis.
  6. Baillie, Richard T & Bollerslev, Tim, 2002. "The Message in Daily Exchange Rates: A Conditional-Variance Tale," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 60-68, January.
  7. Chong, Yock Y & Hendry, David F, 1986. "Econometric Evaluation of Linear Macro-Economic Models," Review of Economic Studies, Wiley Blackwell, vol. 53(4), pages 671-90, August.
  8. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
  9. Whitney K. Newey & Kenneth D. West, 1986. "A Simple, Positive Semi-Definite, Heteroskedasticity and AutocorrelationConsistent Covariance Matrix," NBER Technical Working Papers 0055, National Bureau of Economic Research, Inc.
  10. Christopher Neely & Paul Weller, 1998. "Technical trading rules in the European Monetary System," Working Papers 1997-015, Federal Reserve Bank of St. Louis.
  11. Newey, Whitney K & West, Kenneth D, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," Review of Economic Studies, Wiley Blackwell, vol. 61(4), pages 631-53, October.
  12. Christopher Neely & Paul Weller, 2000. "Technical analysis and central bank intervention," Working Papers 1997-002, Federal Reserve Bank of St. Louis.
  13. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
  14. Neely, Christopher J., 2003. "Risk-adjusted, ex ante, optimal technical trading rules in equity markets," International Review of Economics & Finance, Elsevier, vol. 12(1), pages 69-87.
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Cited by:
  1. Christopher J. Neely, 2004. "Implied volatility from options on gold futures: do statistical forecasts add value or simply paint the lilly?," Working Papers 2003-018, Federal Reserve Bank of St. Louis.
  2. Christopher J. Neely, 2004. "Forecasting foreign exchange volatility: why is implied volatility biased and inefficient? and does it matter?," Working Papers 2002-017, Federal Reserve Bank of St. Louis.

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