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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Paper provided by Umeå University, Department of Economics in its series Umeå Economic Studies with number
562.
Length: 18 pages Date of creation: 01 Jun 2001 Date of revision: Publication status: Published in Applied Economics Letters , 2003, pages 725-728. Handle: RePEc:hhs:umnees:0562
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Find related papers by JEL classification: C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies
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References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Hansen, Bruce E, 1994.
"Autoregressive Conditional Density Estimation,"
International Economic Review,
Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 705-30, August.
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