Work

Autoregressive Conditional Kurtosis

Year: 2005
Type: article
Abstract: This article proposes a new model for autoregressive conditional heteroscedasticity and kurtosis. Via a time-varying degrees of freedom parameter, the conditional variance and conditional kurtosis are permitted to evolve separately. The model uses only the standard Student’s t-density and consequently can be estimated simply using maximum likelihood. The method is applied to a set of four daily financial asset return series comprising U.S. and U.K. stocks and bonds, and significant evidence in favor of the presence of autoregressive conditional kurtosis is observed. Various extensions to the basic model are proposed, and we show that the response of kurtosis to good and bad news is not significantly asymmetric.
Author: C. Brooks
Language: English
Subfield: Finance
Open Access status: green
OpenAlex ID: W2163600634
FWCI: 17.43
Cites: 22
Cited by: 170
Related to: 10