Umeå Economic Studies,
Umeå University, Department of Economics

Abstract: The paper studies two approaches to modelling conditional skewness in a nonlinear model for stock returns. It is found that a normal distribution can be rejected. A log-generalized gamma distribution with one time-varying density parameter, and in particular a Pearson IV specification with three constant parameters are better supported by data. While the log-generalized gamma indicates that time-varying skewness is an important feature of the daily composite returns of NYSE, the Pearson IV model suggests that excess kurtosis rather than skewness should be accounted for.

Keywords: Time series; nonlinearity; Pearson IV; log-generalized gamma; NYSE

JEL-codes: C22; C51; C52; C53; G14

18 pages, June 1, 2001

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Published as

Kurt Brännäs and Niklas Nordman, (2003), 'Conditional Skewness Modelling for Stock Returns', Applied Economics Letters, vol 10, pages 725-728

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