Modeling Conditional Skewness in Stock Returns

Markku Lanne and Saikkonen Pentti

European Journal of Finance, 2007, vol. 13, issue 8, pages 691-704

Abstract: In this paper, we propose a new GARCH-in-Mean (GARCH-M) model allowing for conditional skewness. The model is based on the so-called z distribution capable of modeling skewness and kurtosis of the size typically encountered in stock return series. The need to allow for skewness can also be readily tested. The model is consistent with the volatility feedback effect in that conditional skewness is dependent on conditional variance. Compared to previously presented GARCH models allowing for conditional skewness, the model is analytically tractable, parsimonious and facilitates straightforward interpretation.Our empirical results indicate the presence of conditional skewness in the monthly postwar US stock returns. Small positive news is also found to have a smaller impact on conditional variance than no news at all. Moreover, the symmetric GARCH-M model not allowing for conditional skewness is found to systematically overpredict conditional variance and average excess returns.

Keywords: GARCH; conditional skewness; asset pricing (search for similar items in EconPapers)

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Working Paper: Modeling Conditional Skewness in Stock Returns (2005)
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