Conditional Skewness Modelling for Stock Returns
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.
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|Date of creation:||01 Jun 2001|
|Publication status:||Published in Applied Economics Letters , 2003, pages 725-728.|
|Contact details of provider:|| Postal: Department of Economics, Umeå University, S-901 87 Umeå, Sweden|
Phone: 090 - 786 61 42
Fax: 090 - 77 23 02
Web page: http://www.econ.umu.se/
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