Cross-sectional Learning of Extremal Dependence Among Financial Assets

@article{Yan2019CrosssectionalLO,
  title={Cross-sectional Learning of Extremal Dependence Among Financial Assets},
  author={Xing Yan and Qi Wu and Wen Zhang},
  journal={Computational Materials Science eJournal},
  year={2019}
}
  • Xing Yan, Qi Wu, Wen Zhang
  • Published 2019
  • Computer Science, Economics, Mathematics
  • Computational Materials Science eJournal
We propose a novel probabilistic model to facilitate the learning of multivariate tail dependence of multiple financial assets. Our method allows one to construct from known random vectors, e.g., standard normal, sophisticated joint heavy-tailed random vectors featuring not only distinct marginal tail heaviness, but also flexible tail dependence structure. The novelty lies in that pairwise tail dependence between any two dimensions is modeled separately from their correlation, and can vary… Expand
5 Citations

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