We propose a new approach to evaluating copula-based multivariate density forecasts. Employing Hansen’s SPA test and conducting multiple comparisons of fully-parametric models, our approach accommodates possible misspecifications in the multivariate joint and the univariate marginal...

We introduce a statistical test for comparing the predictive accuracy of competing copula specifications in multivariate density forecasts, based on the Kullback-Leibler Information Criterion (KLIC). The test is valid under general conditions: in particular it allows for parameter estimation...

The unprecedented fiscal and monetary policy responses during the COVID-19 crisis have increased uncertainty about inflation. During crises periods, the strength of the transmission of inflation uncertainty shocks from one country to another tends to intensify. This paper examines empirical...

In this paper we present a forecasting method for time series using copula-based models for multivariate time series. We study how the performance of the predictions evolve when changing the strength of the different possible dependencies, as well as the structure of the dependence. We also look...

There is a growing interest in allowing for asymmetry in the density forecasts of macroeconomic variables. In multivariate time series, this can be achieved with a copula model, where both serial and cross-sectional dependence is captured by a copula function, and the margins are nonparametric....

In the increasingly connected world, many systems are more or less coupled with each other in various ways. A typical example is the cross-market portfolio management, where the products of heterogeneous markets are selected and configured for investment. In such cross-market problems, one...

Accurate estimation of different risk measures for financial portfolios is of utmost importance equally for financial institutions as well as regulators, however, many existing models fail to incorporate any high dimensional dependence structures adequately. To overcome this problem and capture...