Sökning: "asymmetric tail dependence"

Hittade 3 avhandlingar innehållade orden asymmetric tail dependence.

  1. 1. Copula-based Portfolio Optimization

    Författare :Maziar Sahamkhadam; Andreas Stephan; Håkan Locking; Ranadeva Jayasekera; Linnéuniversitetet; []
    Nyckelord :SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; Copula; portfolio optimization; conditional Value-at-Risk; vine copulas; asymmetric tail dependence; Black-Litterman approach; expectile Value-at-Risk; multiobjective portfolios; Business administration; Företagsekonomi;

    Sammanfattning : This thesis studies and develops copula-based portfolio optimization. The overall purpose is to clarify the effects of copula modeling for portfolio allocation andsuggest novel approaches for copula-based optimization. The thesis is a compilation of five papers. LÄS MER

  3. 2. Bayesian inference for high dimensional factor copula models

    Författare :Hoang Nguyen; Maria Conception Ausin Olivera; Pedro Galeano San Miguel; Universidad Carlos III de Madrid; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES;

    Sammanfattning : Copulas have been applied to many research areas as multivariate probability distributions for non-linear dependence structures. However, extending copula functions in high dimensions is challenging due to the increase of model parameters and computational intensity. LÄS MER

  4. 3. Bayesian Modeling of Conditional Densities

    Författare :Feng Li; Mattias Villani; Sylvia Frühwirth-Schnatter; Stockholms universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Bayesian inference; Density estimation; smooth mixtures; surface regression; copulas; Markov chain Monte Carlo; Statistics; statistik;

    Sammanfattning : This thesis develops models and associated Bayesian inference methods for flexible univariate and multivariate conditional density estimation. The models are flexible in the sense that they can capture widely differing shapes of the data. The estimation methods are specifically designed to achieve flexibility while still avoiding overfitting. LÄS MER