Copulas and their uses in statistics, namely biostatistics, are a relatively new field of research. When modeling the dependence structure between a vector random variable's joint distribution and marginal distributions, copulas are crucial. In this article, we discuss recent research on this...

We examine tail dependence between consumer sentiment and spending during crises, focusing on COVID-19 and the Global Financial Crisis. Using copula models on U.S. monthly data from 2003-2024, we quantify extreme co-movements and find asymmetric tail dependence that intensifies during crises:...

This paper investigates tail-risk transmission and asymmetric dependence in commodity markets using an asymmetric fuzzy vine copula framework applied to gold, crude oil, natural gas, and silver from 1 January 2015 to 1 January 2025, extracted from Yahoo Finance. Bootstrap-based trapezoidal fuzzy...

The key assumption of normally distributed error terms is usually not tested in empirical practice when using ordered probit models. Therefore, an artificial regression version of the LM test against the class of Pearson distributions is derived that can be implemented more easily than the...

This paper introduces the Copula Asymmetry Index (CAI), a rolling, rank-based measure of asymmetric tail dependence between equity returns and implied-volatility proxies. CAI is defined as the difference between the empirical frequency of joint "equity-down & volatility-up" tail events and that...

Considering achieving a goal in each of several time intervals when, in every time interval, an adverse event may lead to a failure raises the question of the return probability of adverse events, so the probability of at least one failure to happen during the time period of interest. Through...