Dependence Modeling:Vine Copula Handbook

Edited by Dorota Kurowicka and Harry Joe

in World Scientific Books from World Scientific Publishing Co. Pte. Ltd.

Abstract: 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.

Keywords: Dependence Modeling; Joint Distributions; Copulae; Vines; Graphical Models; PCC (search for similar items in EconPapers)
Date: 2010
ISBN: 9789814299879
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https://www.worldscientific.com/worldscibooks/10.1142/7699 (text/html)
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Chapters in this book:

Ch 1 Introduction: Dependence Modeling , pp 1-17

Dorota Kurowicka

Ch 2 Multivariate Copulae , pp 19-36

Matthias Fischer

Ch 3 Vines Arise , pp 37-71

Roger Cooke, Harry Joe and Kjersti Aas

Ch 4 Sampling Count Variables with Specified Pearson Correlation: A Comparison Between a Naive and a C-Vine Sampling Approach , pp 73-87

Vinzenz Erhardt and Claudia Czado

Ch 5 Micro Correlations and Tail Dependence , pp 89-112

Roger Cooke, Carolyn Kousky and Harry Joe

Ch 6 The Copula Information Criterion and Its Implications for the Maximum Pseudo-Likelihood Estimator , pp 113-138

Steffen Grønneberg

Ch 7 Dependence Comparisons of Vine Copulae with Four or More Variables , pp 139-164

Harry Joe

Ch 8 Tail Dependence in Vine Copulae , pp 165-187

Harry Joe

Ch 9 Counting Vines , pp 189-218

O. Morales-Nápoles

Ch 10 Regular Vines: Generation Algorithm and Number of Equivalence Classes , pp 219-231

Harry Joe, Roger Cooke and Dorota Kurowicka

Ch 11 Optimal Truncation of Vines , pp 233-247

Dorota Kurowicka

Ch 12 Bayesian Inference for D-Vines: Estimation and Model Selection , pp 249-264

Claudia Czado and Aleksey Min

Ch 13 Analysis of Australian Electricity Loads Using Joint Bayesian Inference of D-Vines with Autoregressive Margins , pp 265-280

Claudia Czado, Florian Gärtner and Aleksey Min

Ch 14 Non-Parametric Bayesian Belief Nets versus Vines , pp 281-303

Anca Hanea

Ch 15 Modeling Dependence Between Financial Returns Using Pair-Copula Constructions , pp 305-328

Kjersti Aas and Daniel Berg

Ch 16 Dynamic D-Vine Model , pp 329-353

Andréas Heinen and Alfonso Valdesogo Robles

Ch 17 Summary and Future Directions , pp 355-357

Dorota Kurowicka

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