Simulating Copulas: Stochastic Models, Sampling Algorithms, And Applications (Second Edition‪)‬

The book provides the background on simulating copulas and multivariate distributions in general. It unifies the scattered literature on the simulation of various families of copulas (elliptical, Archimedean, Marshall-Olkin type, etc.) as well as on different construction principles (factor models, pair-copula construction, etc.). The book is self-contained and unified in presentation and can be used as a textbook for graduate and advanced undergraduate students with a firm background in stochastics. Besides the theoretical foundation, ready-to-implement algorithms and many examples make the book a valuable tool for anyone who is applying the methodology.
Contents:IntroductionArchimedean CopulasMarshall–Olkin CopulasElliptical CopulasPair Copula ConstructionsSampling Univariate Random VariablesThe Monte Carlo MethodFurther Copula Families with Known Extendible SubclassAppendix: Supplemental Material
Readership: Advanced undergraduate and graduate students in probability calculus and stochastics, practitioners who implement models in the financial industry and scientists.
Copula;Simulation;Monte Carlo;Random Vector;Dependence ModelKey Features:Explicit focus on stochastic representations of copulas in contrast to an analytical perspectiveEasy-to-implement simulation schemes given as pseudo codeExplicit focus on high-dimensional modelsFocus on applicability of models, e.g. to portfolio credit risk or insurance