We propose a multidimensional extension for Patton's (2006) bivariate Dynamic Copulas. We also introduce a Dynamic Mixture Copula whose parameters and weights follow well defined dynamic processes. Both approaches are more flexible to adapt to financial data than currently available Copula...

This paper proposes a new class of dynamic copula models for daily asset returns that exploits information from high frequency (intra-daily) data. We augment the generalized autoregressive score (GAS) model of Creal, et al. (2012) with high frequency measures such as realized correlation to...

We propose and backtest a multivariate Value-at-Risk model for financial returns based on Tukey's g-and-h distribution. This distributional assumption is especially useful if (conditional) asymmetries as well as heavy tails have to be considered and fast random sampling is of importance. To...

Recently, several copula-based approaches have been proposed for modeling stationary multivariate time series. All of them are based on vine copulas, and they differ in the choice of the regular vine structure. In this article, we consider a copula autoregressive (COPAR) approach to model the...

We investigate the dependence structure between Polish and foreign financial assets, including stocks, bonds and foreign exchange. Our interest is in the importance of global factors for asset valuation and on the strength of financial contagion. We work in the copula framework, which offers a...

This paper derives -- considering a Gaussian setting -- closed form solutions of the statistics that Adrian and Brunnermeier (2010) and Acharya et al. (2009) have suggested as measures of systemic risk to be attached to individual banks. The statistics equal the product of statistic specific...

This study uses the Multiplicative Error Model (MEM) to explore asymmetric volatility spillovers between crude oil and other major asset markets. We have extended the MEM of Engle et al. (2012) and ddd to include asymmetric volatility spillovers and developed the spillover balance as well as...

We introduce a copula-based dynamic model for multivariate processes of (non-negative) high-frequency trading variables revealing time-varying conditional variances and correlations. Modeling the variables' conditional mean processes using a multiplicative error model we map the resulting...