An Econometric Study of Vine Copulas
We present a new recursive algorithm to construct vine copulas based on an underlying tree structure. This new structure is interesting to compute multivariate distributions for dependent random variables. We proove the asymptotic normality of the vine copula parameter estimator and show that all vine copula parameter estimators have comparable variance. Both results are crucial to motivate any econometrical work based on vine copulas. We provide an application of vine copulas to estimate the VaR of a portfolio, and show they offer significant improvement as compared to a benchmark estimator based on a GARCH model
|Date of creation:||May 2010|
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LSE Research Online Documents on Economics
24681, London School of Economics and Political Science, LSE Library.
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wp04-04, Warwick Business School, Finance Group.
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"New prospects on vines,"
Documents de travail du Centre d'Economie de la Sorbonne
b08095, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Mar 2010.
- Dominique Guegan & Pierre-André Maugis, 2010. "New Prospects on Vines," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00348884, HAL.
- Andrew J. Patton, 2008. "Copula-Based Models for Financial Time Series," OFRC Working Papers Series 2008fe21, Oxford Financial Research Centre.
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