This paper provides a simple, yet reliable, alternative to the (Bayesian) estimation of large multivariate VARs with time variation in the conditional mean equations and/or in the covariance structure. With our new methodology, the original multivariate, n-dimensional model is treated as a set...

We employ and examine vine copulas in modeling symmetric and asymmetric dependency structures and forecasting financial returns. We analyze the asset allocations performed during the 2008–2009 financial crisis and test different portfolio strategies such as maximum Sharpe ratio, minimum...

The quantity theory of money remains a cornerstone of modern macroeconomics that provides a benchmark for the long-run behaviour of macroeconomic models. The direct empirical evidence for it is, however, less conclusive than suggested by scatterplots and the exaggerated correlations between...

The existing literature of copula-based regression assumes that complete data are available, but this assumption is violated in many real applications. The present paper allows the regressand and regressors to be missing at random (MAR). We formulate a generalized regression model which unifies...

This paper proposes a novel copula-based local Kendall's tau framework to uncover richer nonlinear local dependence between two financial return series. This framework nests the concepts of global dependence, tail dependence and local dependence. Closed form solutions of local Kendall's tau in...

An alternative generating mechanism for non-strict bivariate Archimedean copulas via the Lorenz curve of a positive random variable is proposed. Lorenz curves have been extensively studied in economics and statistics to characterize wealth inequality and tail risk. In this paper, these curves...