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Evaluating non-linear models on point and interval forecasts: an application with exchange rate returns

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Author Info
Gianna Boero ()
Emanuela Marrocu ()

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Abstract

The aim of this paper is to compare the forecasting performance of SETAR and GARCH models against a linear benchmark using historical data for the returns of the Japanese yen/US dollar exchange rate. The relative performance of the models is evaluated on point forecasts and on interval forecasts. Point forecasts evaluation over the whole forecast period indicates that the performance of the models, when distinguishable, tends to favour the linear models. However, we show that if the evaluation of point forecasts is conducted over distinct subsamples or specific regimes there is more evidence of forecasting gains, especially from the SETAR models. Moreover, when we evaluate the validity of interval forecasts, the results produce clear evidence of the superiority of the non-linear models, and tend to favour especially the GARCH models.

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Paper provided by Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia in its series Working Paper CRENoS with number 200110.

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Date of creation: 2001
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Handle: RePEc:cns:cnscwp:200110

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Related research
Keywords: nonlinearity asymmetry forecasting accuracy point forecasts interval forecasts exchange rates

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Find related papers by JEL classification:
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation

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  1. Clements, Michael P & Smith, Jeremy, 1999. "A Monte Carlo Study of the Forecasting Performance of Empirical SETAR Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(2), pages 123-41, March-Apr. [Downloadable!]
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  2. Clements, Michael P. & Smith, Jeremy, 1997. "The performance of alternative forecasting methods for SETAR models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 463-475, December. [Downloadable!] (restricted)
  3. Boero, Gianna & Marrocu, Emanuela, 2002. "The Performance of Non-linear Exchange Rate Models: A Forecasting Comparison," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(7), pages 513-42, November.
  4. Meese, Richard A & Rose, Andrew K, 1991. "An Empirical Assessment of Non-linearities in Models of Exchange Rate Determination," Review of Economic Studies, Blackwell Publishing, vol. 58(3), pages 603-19, May. [Downloadable!] (restricted)
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  5. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September. [Downloadable!] (restricted)
  6. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March. [Downloadable!] (restricted)
  7. Lawrence R. Glosten & Ravi Jagannathan & David E. Runkle, 1993. "On the relation between the expected value and the volatility of the nominal excess return on stocks," Staff Report 157, Federal Reserve Bank of Minneapolis. [Downloadable!]
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  8. Diebold, Francis X. & Nason, James A., 1990. "Nonparametric exchange rate prediction?," Journal of International Economics, Elsevier, vol. 28(3-4), pages 315-332, May. [Downloadable!] (restricted)
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  9. Krager, Horst & Kugler, Peter, 1993. "Non-linearities in foreign exchange markets: a different perspective," Journal of International Money and Finance, Elsevier, vol. 12(2), pages 195-208, April. [Downloadable!] (restricted)
  10. Wallis, Kenneth F., 2002. "Chi-squared tests of interval and density forecasts, and the Bank of England's fan charts," Royal Economic Society Annual Conference 2002 181, Royal Economic Society. [Downloadable!]
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  11. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March. [Downloadable!] (restricted)
  12. Clements, Michael P. & Smith, Jeremy, 2001. "Evaluating forecasts from SETAR models of exchange rates," Journal of International Money and Finance, Elsevier, vol. 20(1), pages 133-148, February. [Downloadable!] (restricted)
  13. Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-62, November.
  14. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April. [Downloadable!] (restricted)
  15. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
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  16. Gianna Boero & Emanuela Marrocu, 1999. "Modelli non lineari per i tassi di cambio: un confronto previsivo," Working Paper CRENoS 199914, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia. [Downloadable!]
  17. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July. [Downloadable!] (restricted)
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  1. Gianna Boero & Emanuela Marrocu, 2002. "The performance of Setar Models: a regime conditional evaluation of point, interval and density forecasts," Working Paper CRENoS 200208, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia. [Downloadable!]
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