6533b833fe1ef96bd129c119
RESEARCH PRODUCT
Modeling Conditional Skewness in Stock Returns
Markku LannePentti Saikkonensubject
050208 financeAutoregressive conditional heteroskedasticity05 social sciencesEconomics Econometrics and Finance (miscellaneous)Skewness0502 economics and businessStatisticsEconomicsEconometricsKurtosisCapital asset pricing model050207 economicsVolatility (finance)Excess returnConditional varianceStock (geology)description
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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2007-12-01 | The European Journal of Finance |