• Corpus ID: 126059013

Data driven partition-of-unity copulas with applications to risk management

@article{Pfeifer2017DataDP,
  title={Data driven partition-of-unity copulas with applications to risk management},
  author={Dietmar Pfeifer and Andreas Mandle and Olena Ragulina},
  journal={arXiv: Risk Management},
  year={2017}
}
We present a constructive and self-contained approach to data driven general partition-of-unity copulas that were recently introduced in the literature. In particular, we consider Bernstein-, negative binomial and Poisson copulas and present a solution to the problem of fitting such copulas to highly asymmetric data. 

Bayesian estimation of generalized partition of unity copulas

A Bayesian estimation algorithm to estimate Generalized Partition of Unity Copulas (GPUC), a class of nonparametric copulas recently introduced by [18], and presents an empirical illustration where GPUCs are used to nonparametrically describe the dependence of exchange rate changes of the crypto-currencies Bitcoin and Ethereum.

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