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Improving Garch Volatility Forecasts

Listed author(s):
  • Klaassen, F.J.G.M.

    (Tilburg University, Center For Economic Research)

Many researchers use GARCH models to generate volatility forecasts. We show, however, that such forecasts are too variable. To correct for this, we extend the GARCH model by distinguishing two regimes with different volatility levels. GARCH effects are allowed within each regime, so that our model generalizes existing regime-switching models that allow for ARCH terms only. The empirical application on U.S. dollar exchange rates shows that our model indeed yields better volatility forecasts than single-regime GARCH and that the allowance for GARCH terms besides ARCH terms can be crucial for the forecast quality.

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File URL: https://pure.uvt.nl/portal/files/529207/52.pdf
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Paper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 1998-52.

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Date of creation: 1998
Handle: RePEc:tiu:tiucen:f5bcd096-7744-4137-aabc-6a305c6266d9
Contact details of provider: Web page: http://center.uvt.nl

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  1. Pagan, Adrian R. & Schwert, G. William, 1990. "Alternative models for conditional stock volatility," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 267-290.
  2. Torben G. Andersen & Tim Bollerslev, 1997. "Answering the Critics: Yes, ARCH Models Do Provide Good Volatility Forecasts," NBER Working Papers 6023, National Bureau of Economic Research, Inc.
  3. Hakkio, Craig S. & Rush, Mark, 1989. "Market efficiency and cointegration: an application to the sterling and deutschemark exchange markets," Journal of International Money and Finance, Elsevier, vol. 8(1), pages 75-88, March.
  4. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
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