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Forecasting the Volatility of Australian Stock Returns: Do Common Factors Help?

  • Anderson, Heather M.
  • Vahid, Farshid

This paper develops univariate and multivariate forecasting models for realized volatility in Australian stocks. We consider multivariate models with common features or common factors, and we suggest estimation procedures for approximate factor models that are robust to jumps when the cross-sectional dimension is not very large. Our forecast analysis shows that multivariate models outperform univariate models, but that there is little difference between simple and sophisticated factor models.

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Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

Volume (Year): 25 (2007)
Issue (Month): (January)
Pages: 76-90

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Handle: RePEc:bes:jnlbes:v:25:y:2007:p:76-90
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  17. Harvey, Andrew & Ruiz, Esther & Shephard, Neil, 1994. "Multivariate Stochastic Variance Models," Review of Economic Studies, Wiley Blackwell, vol. 61(2), pages 247-64, April.
  18. Engle, Robert F. & Marcucci, Juri, 2006. "A long-run Pure Variance Common Features model for the common volatilities of the Dow Jones," Journal of Econometrics, Elsevier, vol. 132(1), pages 7-42, May.
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