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Copulas in Finance and Insurance
Elisa M. Molanes and Rosario Romera |
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Copulas provide a potential useful modeling tool to represent the dependence structure
among variables and to generate joint distributions by combining given marginal distributions.
Simulations play a relevant role in finance and insurance. They are used to replicate efficient
frontiers or extremal values, to price options, to estimate joint risks, and so on. Using copulas, it
is easy to construct and simulate from multivariate distributions based on almost any choice of
marginals and any type of dependence structure. In this paper we outline recent contributions of
statistical modeling using copulas in finance and insurance. We review issues related to the notion
of copulas, copula families, copula-based dynamic and static dependence structure, copulas and
latent factor models and simulation of copulas. Finally, we outline hot topics in copulas with a
special focus on model selection and goodness-of-fit testing.
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