This book offers a thorough understanding of Hierarchical Archimedean Copulas (HACs) and their practical applications. It covers the basics of copulas, explores the Archimedean family, and delves into the specifics of HACs, including their fundamental properties. The text also addresses sampling algorithms, HAC parameter estimation, and structure, and highlights temporal models with applications in finance and economics. The final chapter introduces R, MATLAB, and Octave toolboxes for copula modeling, enabling students, researchers, data scientists, and practitioners to model complex dependence structures and make well-informed decisions across various domains.
This book offers a thorough understanding of Hierarchical Archimedean Copulas (HACs) and their practical applications. It covers the basics of copulas, explores the Archimedean family, and delves into the specifics of HACs, including their fundamental properties. The text also addresses sampling algorithms, HAC parameter estimation, and structure, and highlights temporal models with applications in finance and economics. The final chapter introduces R, MATLAB, and Octave toolboxes for copula modeling, enabling students, researchers, data scientists, and practitioners to model complex dependence structures and make well-informed decisions across various domains.
Broadens understanding of copulas, with a focus on Hierarchical Archimedean Copulas, and their applications Provides the knowledge and tools for modeling complex dependence structures Features exercises and a chapter on software toolboxes for copula modeling
Jan Górecki
Hierarchical Archimedean Copulas Copulas Archimedean Copulas Dependence Modeling Temporal Models Copula Software Copula Modeling HACs Sampling Algorithms HAC Parameter Estimation Copulas in Finance and Economics