In this paper, we compare the Constant Conditional Correlation (CCC) model to its dynamic counterpart, the Dynamic Conditional Correlation (DCC) model with respect to its accuracy for forecasting the Value-at-Risk of financial portfolios. Additionally, we modify these benchmark models by...

We propose two new tests for detecting clustering in multivariate Value-at-Risk (VaR) forecasts. First, we consider CUSUM-tests to detect first-order instationarities in the matrix of VaR-violations. Second, we propose x²-tests for detecting cross-sectional and serial dependence in the...

We show that liquidity tail risk in credit default swap (CDS) spreads is time-varying and explains variation in CDS spreads. We capture the liquidity tail risk of a CDS contract written on a firm by estimating the tail dependence, i.e., the asymptotic probability of a joint surge in the bid-ask...

We propose to model the joint distribution of bid-ask spreads and log returns of a stock portfolio by using Autoregressive Conditional Double Poisson and GARCH processes for the marginals and vine copulas for the dependence structure. By estimating the joint multivariate distribution of both...

We propose a new set of formal backtests for VaR-forecasts that significantly improve upon existing backtesting procedures. Our new test of unconditional coverage can be used for both one-sided and two-sided testing, which leads to a significantly increased power. Second, we stress the...