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.
