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Forecasting variance using stochastic volatility and GARCH

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Author Info

  • 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.

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File URL: http://www.tandfonline.com/doi/abs/10.1080/1351847021000025803
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Bibliographic Info

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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Related research

Keywords: Variance; stochastic volatility; GARCH models; forecasting ability; weekend/holiday effects;

References

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  16. Scott, Louis O., 1987. "Option Pricing when the Variance Changes Randomly: Theory, Estimation, and an Application," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(04), pages 419-438, December.
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Citations

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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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