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Backtesting Value-at-Risk Estimation With Non Gaussian Marginals
Company: University of Cagliari
Year Of Publication: 2004
Month Of Publication: May
Pages: 18
Download Count: 497
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Comment Num: 0
Language: EN
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Who Can Read: Free
Date: 2-8-2007
Publisher: Administrator
Summary
This paper uses copula functions to model dependence structure amongst stock returns, dropping the jointnormality assumption with the aim of calculating the Value at Risk (VAR) of a stock portfolio.In this way we are able to represent distribution functions separating the marginal distributions from theassociation structure.We present here two different applications.In the first one we apply the methodology (and we also present all the necessary algorithms) to a three riskyassets portfolio using non gaussian marginal probability distributions and a dependence structure modelledby an Archimedean or a Student copula function. In this way we are able to obtain the joint distribution ofthe three asset portfolio and to calculate the probability of extreme losses.The empirical results of this first application are then verified and compared with a traditional Monte Carlosimulation using various backtesting techniques.On the evidence of the empirical results of the first application, we apply our scheme of VAR valuation totwo large and realistic portfolios of stocks, the first one formed by 14 Italian stocks and the second one by22.Also in this example, we perform backtesting calculation on a large time period showing that the copulaapproach gives more reliable results in comparison with the traditional valuations.
Author(s)
Micocci, Marco Sign in to follow this author
Masala, Giovanni Sign in to follow this author
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