Vine copulas: modelling systemic risk and enhancing higher‐moment portfolio optimisation
نویسندگان
چکیده
منابع مشابه
Risk Measurement and Risk Modelling Using Applications of Vine Copulas
This paper features an application of Regular Vine copulas which are a novel and recently developed statistical and mathematical tool which can be applied in the assessment of composite financial risk. Copula-based dependence modelling is a popular tool in financial applications, but is usually applied to pairs of securities. By contrast, Vine copulas provide greater flexibility and permit the ...
متن کاملSelection of Vine Copulas
Vine copula models have proven themselves as a very flexible class of multivariate copula models with regard to symmetry and tail dependence for pairs of variables. The full specification of a vine model requires the choice of vine tree structure, copula families for each pair copula term and their corresponding parameters. In this survey we discuss the different approaches, both frequentist as...
متن کاملApproximate Uncertainty Modeling in Risk Analysis with Vine Copulas
Many applications of risk analysis require us to jointly model multiple uncertain quantities. Bayesian networks and copulas are two common approaches to modeling joint uncertainties with probability distributions. This article focuses on new methodologies for copulas by developing work of Cooke, Bedford, Kurowica, and others on vines as a way of constructing higher dimensional distributions tha...
متن کاملTail dependence functions and vine copulas
Tail dependence and conditional tail dependence functions describe, respectively, the tail probabilities and conditional tail probabilities of a copula at various relative scales. The properties as well as the interplay of these two functions are established based upon their homogeneous structures. The extremal dependence of a copula, as described by its extreme value copulas, is shown to be co...
متن کاملKeyCredit risk, Portfolio credit risk model, Portfolio optimisation, Genetic
This paper proposes a new combination of quantitative models and Genetic Algorithms for the task of optimising credit portfolios. Currently, quantitative portfolio credit risk models are used to calculate portfolio risk figures, e. g. expected losses, unexpected losses and risk contributions. Usually, this information is used for optimising the risk-return profile of the portfolio. We show that...
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ژورنال
عنوان ژورنال: Accounting & Finance
سال: 2017
ISSN: 0810-5391,1467-629X
DOI: 10.1111/acfi.12274