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Which Parametric Model for Conditional Skewness?

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  • Bruno Feunou
  • Mohammad R. Jahan-Parvar
  • Roméo Tedongap

Abstract

This paper addresses an existing gap in the developing literature on conditional skewness. We develop a simple procedure to evaluate parametric conditional skewness models. This procedure is based on regressing the realized skewness measures on model-implied conditional skewness values. We find that an asymmetric GARCH-type specification on shape parameters with a skewed generalized error distribution provides the best in-sample fit for the data, as well as reasonable predictions of the realized skewness measure. Our empirical findings imply significant asymmetry with respect to positive and negative news in both conditional asymmetry and kurtosis processes.

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File URL: http://www.bankofcanada.ca/wp-content/uploads/2013/09/wp2013-32.pdf
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Bibliographic Info

Paper provided by Bank of Canada in its series Working Papers with number 13-32.

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Length: 44 pages
Date of creation: 2013
Date of revision:
Handle: RePEc:bca:bocawp:13-32

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Keywords: Econometric and statistical methods;

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References

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  16. Kim, Tae-Hwan & White, Halbert, 2004. "On more robust estimation of skewness and kurtosis," Finance Research Letters, Elsevier, vol. 1(1), pages 56-73, March.
  17. Chernov, Mikhail, 2007. "On the Role of Risk Premia in Volatility Forecasting," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 411-426, October.
  18. Anthony Neuberger, 2012. "Realized Skewness," Review of Financial Studies, Society for Financial Studies, vol. 25(11), pages 3423-3455.
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