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Modeling and forecasting outliers and level shifts in absolute returns

Author

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  • Franses, Ph.H.B.F.
  • van der Leij, M.J.
  • Paap, R.

Abstract

Due to high and low volatility periods, time series of absolute returns experience temporary level shifts (that is, periods with outliers) which differ in length and size. In this paper we put forward a new model which can describe and forecast the location and size of such level shifts. Our so called Switching Regime Censored Latent Effects Autoregression [SR-CLEAR] assumes that technical trading rules may have explanatory value for future volatility. It is assumed that these rules have a time-varying effect on absolute returns, and that this effect appears as an outlier or a level shift. We apply the SR-CLEAR model to nine stock markets and we document its excellent fit and competitive forecasting ability.

Suggested Citation

  • Franses, Ph.H.B.F. & van der Leij, M.J. & Paap, R., 2001. "Modeling and forecasting outliers and level shifts in absolute returns," Econometric Institute Research Papers EI 2001-34, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Handle: RePEc:ems:eureir:1701
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    Cited by:

    1. Elena Andreou & Eric Ghysels, 2002. "Detecting multiple breaks in financial market volatility dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 579-600.
    2. Richard Paap & Philip Hans Franses & Marco Van Der Leij, 2002. "Modelling and forecasting level shifts in absolute returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 601-616.

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