Description

Book Synopsis
This book is a collaborative effort from three workshops held over the last three years, all involving principal contributors to the vine-copula methodology. Research and applications in vines have been growing rapidly and there is now a growing need to collate basic results, and standardize terminology and methods. Specifically, this handbook will (1) trace historical developments, standardizing notation and terminology, (2) summarize results on bivariate copulae, (3) summarize results for regular vines, and (4) give an overview of its applications. In addition, many of these results are new and not readily available in any existing journals. New research directions are also discussed.

Table of Contents
Introduction; Multivariate Copulae; Vine Copulae; Sampling Count Variables; Micro Correlations and Tail Dependence; Copula Information Criterion; Dependence Comparisons of Vine Copulae; Tail Dependence in Vine Copulae; Counting Vines; Optimal Truncation of Vines; Non-Parametric BBNs vs. Vines; Joint Bayesian Inference of D-Vines with AR(1) Margins; Modeling Dependence Between Financial Returns Using PCC; Dynamic D-Vine Model; Regular Vines: Generation Algorithm and Number of Equivalent Classes;

Dependence Modeling: Vine Copula Handbook

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    A Hardback by Dorota Kurowicka, Harry Joe

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      Book details

      Publisher World Scientific Publishing Co Pte Ltd
      Published 27 December 2010
      ISBN-13 9789814299879
      978-9814299879
      ISBN-10 9814299871
      Also in:
      Probability and statistics

      Description

      Book Synopsis
      This book is a collaborative effort from three workshops held over the last three years, all involving principal contributors to the vine-copula methodology. Research and applications in vines have been growing rapidly and there is now a growing need to collate basic results, and standardize terminology and methods. Specifically, this handbook will (1) trace historical developments, standardizing notation and terminology, (2) summarize results on bivariate copulae, (3) summarize results for regular vines, and (4) give an overview of its applications. In addition, many of these results are new and not readily available in any existing journals. New research directions are also discussed.

      Table of Contents
      Introduction; Multivariate Copulae; Vine Copulae; Sampling Count Variables; Micro Correlations and Tail Dependence; Copula Information Criterion; Dependence Comparisons of Vine Copulae; Tail Dependence in Vine Copulae; Counting Vines; Optimal Truncation of Vines; Non-Parametric BBNs vs. Vines; Joint Bayesian Inference of D-Vines with AR(1) Margins; Modeling Dependence Between Financial Returns Using PCC; Dynamic D-Vine Model; Regular Vines: Generation Algorithm and Number of Equivalent Classes;

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