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Forecasting variance using stochastic volatility and GARCH

  • Bjorn Hansson
  • Peter Hordahl

This paper estimates the conditional variance of daily Swedish OMX-index returns with stochastic volatility (SV) models and GARCH models and evaluates the in-sample performance as well as the out-of-sample forecasting ability of the models. Asymmetric as well as weekend/holiday effects are allowed for in the variance, and the assumption that errors are Gaussian is released. Evidence is found of a leverage effect and of higher variance during weekends. In both in-sample and out-of-sample comparisons SV models outperform GARCH models. However, while asymmetry, weekend/holiday effects and non-Gaussian errors are important for the in-sample fit, it is found that these factors do not contribute to enhancing the forecasting ability of the SV models.

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Article provided by Taylor & Francis Journals in its journal The European Journal of Finance.

Volume (Year): 11 (2005)
Issue (Month): 1 ()
Pages: 33-57

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Handle: RePEc:taf:eurjfi:v:11:y:2005:i:1:p:33-57
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