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Mixture pair-copula-constructions
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DOI：10.1016/j.jbankfin.2015.01.008.png)
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We propose the use of convex combinations of parametric copulas as pair-copulas in high-dimensional vine copula models. By doing so, we circumvent the error-prone need to choose and estimate a parametric copula for each pair-copula in a vine model. We show in simulations that our proposed model fits the dependence structure in a given data sample significantly better than a competing benchmark. In our empirical study on the models' accuracy for forecasting the Value-at-Risk of financial portfolios, we show that our proposed mixture pair-copula construction yields significantly better results in backtesting while the benchmark overestimates portfolio risk. (C) 2015 Elsevier B.V. All rights reserved.
Keyword:
Dependence structures
Vine copulas
Mixture copulas
Model selection
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