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Modeling asymmetric volatility in weekly Dutch temperature data

Author

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  • Franses, Ph.H.B.F.
  • Neele, J.
  • van Dijk, D.J.C.

Abstract

In addition to clear-cut seasonality in mean and variance, weekly Dutch temperature data appear to have a strong asymmetry in the impact of unexpectedly high or low temperatures on conditional volatility. Furthermore, this asymmetry also shows fairly pronounced seasonal variation. To describe these features, we propose a univariate seasonal time series model with asymmetric conditionally heteroskedastic errors. We fit this (and other, nested) model(s) to 25 years of weekly data. We evaluate its forecasting performance for 5 years of hold-out data and find that the imposed asymmetry leads to better out-of-sample forecasts of temperature volatility.

Suggested Citation

  • Franses, Ph.H.B.F. & Neele, J. & van Dijk, D.J.C., 1998. "Modeling asymmetric volatility in weekly Dutch temperature data," Econometric Institute Research Papers EI 9840, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:1533
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    References listed on IDEAS

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