Regular variation and extremal dependence of GARCH residuals with application to market risk measures

Laurini, Fabrizio and Tawn, Jonathan A. (2009) Regular variation and extremal dependence of GARCH residuals with application to market risk measures. Econometric Reviews, 28 (1-3). pp. 146-169. ISSN 0747-4938

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Abstract

Stock returns exhibit heavy tails and volatility clustering. These features, motivating the use of GARCH models, make it difficult to predict times and sizes of losses that might occur. Estimation of losses, like the Value-at-Risk, often assume that returns, normalized by the level of volatility, are Gaussian. Often under ARMA-GARCH modeling, such scaled returns are heavy tailed and show extremal dependence, whose strength reduces when increasing extreme levels. We model heavy tails of scaled returns with generalized Pareto distributions, while extremal dependence can be reduced by declustering data.

Item Type:
Journal Article
Journal or Publication Title:
Econometric Reviews
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2000/2002
Subjects:
ID Code:
177762
Deposited By:
Deposited On:
18 Oct 2022 10:45
Refereed?:
Yes
Published?:
Published
Last Modified:
22 Nov 2022 11:58