A g-and-h copula approach to risk measurement in multivariate financial models

Huggenberger, Markus ; Klett, Timo

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URL: https://ub-madoc.bib.uni-mannheim.de/3121
URN: urn:nbn:de:bsz:180-madoc-31218
Document Type: Working paper
Year of publication: 2010
The title of a journal, publication series: Mannheimer Manuskripte zu Risikotheorie, Portfolio Management und Versicherungswirtschaft
Volume: 182
Place of publication: Mannheim
Publication language: English
Institution: Business School > Sonstige - Fakultät für Betriebswirtschaftslehre
MADOC publication series: Lehrstuhl für ABWL, Risikotheorie, Portfolio Management und Versicherungswirtschaft (Albrecht) > Mannheimer Manuskripte zu Risikotheorie, Portfolio Management und Versicherungswirtschaft
Subject: 330 Economics
Classification: JEL: C46 C32 C16 C51 G10 ,
Subject headings (SWD): GARCH-Prozess , Value at Risk , Multivariate Daten , Aktienindex
Keywords (English): g-and-h distribution , copula , GARCH , Value-at-Risk , stock indices , skewed-t distribution
Abstract: We propose and backtest a multivariate Value-at-Risk model for financial returns based on Tukey's g-and-h distribution. This distributional assumption is especially useful if (conditional) asymmetries as well as heavy tails have to be considered and fast random sampling is of importance. To illustrate our methodology, we fit copula GARCH models with g-and-h distributed residuals to three European stock indices and provide results of out-of-sample Value-at-Risk backtests. We find that our g-and-h model outperforms models with less flexible residual distributions and attains similar results as a benchmark model based on Hansen's skewed-t distribution.
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