Entropy Densities with an Application to Autoregressive Conditional Skewness and Kurtosis

Details

Serval ID
serval:BIB_0CCC00C94BA1
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Entropy Densities with an Application to Autoregressive Conditional Skewness and Kurtosis
Journal
Journal of Econometrics
Author(s)
Jondeau E., Rockinger M.
ISSN
0304-4076
Publication state
Published
Issued date
01/2002
Peer-reviewed
Oui
Volume
106
Number
1
Pages
119-142
Language
english
Abstract
The entropy principle yields, for a given set of moments, a density that involves the smallest amount of prior information. We first show how entropy densities may be constructed in a numerically efficient way as the minimization of a potential. Next, for the case where the first four moments are given, we characterize the skewness?kurtosis domain for which densities are defined. This domain is found to be much larger than for Hermite or Edgeworth expansions. Last, we show how this technique can be used to estimate a GARCH model where skewness and kurtosis are time varying. We find that there is little predictability of skewness and kurtosis for weekly data.
Keywords
Semi-nonparametric estimation, Time-varying skewness and kurtosis, GARCH
Create date
19/11/2007 9:28
Last modification date
20/08/2019 12:34
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