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Forecasting variance using stochastic volatility and GARCH

Author

Listed:
  • Bjorn Hansson
  • Peter Hordahl

Abstract

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.

Suggested Citation

  • Bjorn Hansson & Peter Hordahl, 2005. "Forecasting variance using stochastic volatility and GARCH," The European Journal of Finance, Taylor & Francis Journals, vol. 11(1), pages 33-57.
  • Handle: RePEc:taf:eurjfi:v:11:y:2005:i:1:p:33-57
    DOI: 10.1080/1351847021000025803
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    References listed on IDEAS

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    Cited by:

    1. Piotr Wdowinski & Marta Malecka, 2010. "Asymmetry in Volatility: A Comparison of Developed and Transition Stock Markets," CESifo Working Paper Series 2974, CESifo Group Munich.
    2. Amilon, Henrik & Byström, Hans, 1998. "The Search for Chaos and Nonlinearities in Swedish Stock Index Returns," Working Papers 1998:6, Lund University, Department of Economics.

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