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Aggregation of Dependent Risks Using the Koehler–Symanowski Copula Function

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Abstract

This study examines the Koehler and Symanovski copula function with specific marginals, such as the skew Student-t, the skew generalized secant hyperbolic, and the skew generalized exponential power distributions, in modelling financial returns and measuring dependent risks. The copula function can be specified by adding interaction terms to the cumulative distribution function for the case of independence. It can also be derived using a particular transformation of independent gamma functions. The advantage of using this distribution relative to others lies in its ability to model complex dependence structures among subsets of marginals, as we show for aggregate dependent risks of some market indices.

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Authors and Affiliations

  1. Department of Quantitative Methods, University of Siena, Italy

    Paola Palmitesta

  2. Department of Statistical Sciences, University of Padua, Italy

    Corrado Provasi

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  1. Paola Palmitesta
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  2. Corrado Provasi
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Correspondence to Paola Palmitesta.

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Palmitesta, P., Provasi, C. Aggregation of Dependent Risks Using the Koehler–Symanowski Copula Function. Comput Econ 25, 189–205 (2005). https://doi.org/10.1007/s10614-005-6282-9

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  • DOI: https://doi.org/10.1007/s10614-005-6282-9

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