Empirical evidence suggests that asset returns correlate more strongly in bear markets than conventional correlation estimates imply. We propose a method for determining complete tail-correlation matrices based on Value-at-Risk (VaR) estimates. We demonstrate how to obtain more effi cient...

We consider a multivariate Markov-switching GARCH model which allows for regime-specific volatility dynamics, leverage effects, and correlation structures. Stationarity conditions are derived, and consistency of the maximum likelihood estimator (MLE) is established under the assumption of...

This paper extends the stochastic dominance rules for normal mixture distributions derived by Levy and Kaplanski (2015). First, the portfolios under consideration are allowed to follow different regime-switching processes. Second, the results are extended from second- to fourth-order stochastic...

Backtesting value-at-risk forecasts is an important issue. A duration-based approach has recently been proposed by Christoffersen and Pelletier (2004). Their method is very appealing because it allows one to test for both correct conditional and unconditional coverage against quite general...

The goal of this paper is to illuminate the capability of the component GARCH model of Ding and Granger (1996) and Engle and Lee (1999) to reproduce the long memory-type behavior of financial volatility. The potential of this model to capture the long memory dynamics observed in measures of...