Skew T Copula

Skew-t copulas are statistical models used to capture the complex relationships between multiple variables, particularly in situations where data exhibit asymmetry and heavy tails, common in financial markets and other fields. Current research focuses on improving the estimation of high-dimensional skew-t copula models, often employing Bayesian methods like variational inference, and addressing challenges like instability in the estimation of degrees of freedom within mixture models. These advancements enhance the accuracy and robustness of modeling asymmetric dependencies, leading to improved predictive capabilities and applications in areas such as portfolio optimization and risk management.