AI in finance refers to the applications of AI techniques in financial businesses. This area has
attracted attention for decades, with both classic and modern AI techniques applied to …

With the availability of massive multivariate data comes a need to develop flexible
multivariate distribution classes. The copula approach allows marginal models to be …

This book is written for graduate students and researchers, who are interested in using
copula-based models for multivariate data structures. It provides a step-by-step introduction …

This study characterizes the oil market as a nonlinear-switching phenomenon and examines
its dynamics in response to changes in geopolitical risks over low-and high-risk scenarios …

Dependence Modeling with Copulas covers the substantial advances that have taken place
in the field during the last 15 years, including vine copula modeling of high-dimensional …

Unlike previous studies, we employ a relatively newer modelling technique—a time-varying
copula with a switching dependence—to characterise the conditional dependence between …

Regular vine distributions which constitute a flexible class of multivariate dependence
models are discussed. Since multivariate copulae constructed through pair-copula …

This survey reviews the large and growing literature on copula-based models for economic
and financial time series. Copula-based multivariate models allow the researcher to specify …

Flexible multivariate distributions are needed in many areas. The popular multivariate
Gaussian distribution is however very restrictive and cannot account for features like …

Copula-based models provide a great deal of flexibility in modeling multivariate
distributions, allowing the researcher to specify the models for the marginal distributions …