We investigate the consequences for value-at-risk and expected shortfall purposes of using a GARCH filter on various mis-specified processes. In general, we find that the McNeil and Frey (2000) two step procedure has very good forecasting properties. Using an unconditional non filtered tail...

It is well known that the class of strong (Generalized) AutoRegressive Conditional Heteroskedasticity (or GARCH) processes is not closed under contemporaneous aggregation. This paper provides the dynamics followed by the aggregate process when the individual persistence parameters are drawn from...

A resampling method based on the bootstrap and a bias-correction step is developed for improving the Value-at-Risk (VaR) forecasting ability of the normal GARCH model. Compared to the use of more sophisticated GARCH models, the new method is fast, easy to implement, numerically reliable, and,...

We propose a general robust semiparametric bootstrap method to estimate conditional predictive distributions of GARCH-type models. Our approach is based on a robust estimator for the parameters in GARCH-type models and a robustified resampling method for standardized GARCH residuals, which...

We propose a new multivariate GARCH model with Dynamic Conditional Correlations that extends previous models by admitting multivariate thresholds in conditional volatilitiesand correlations. The model estimation is feasible in large dimensions and the positive definiteness of the conditional...

We propose a simple class of semiparametric multivariate GARCH models, allowing for asymmetric volatilities and time-varying conditional correlations. Estimates for time-varying conditional correlations are constructed by means of a convex combination of estimates for averaged correlations...

This empirical study analyzes market and currency risk premia during financial and political crises within the theoretical framework of the international asset pricing model of Adler and Dumas (1983). The econometric specification extends the multivariate GARCH approach of De Santis and Gerard...

We evaluate how non-normality of asset returns and the temporal evolution of volatility and higher moments affects the conditional allocation of wealth. We show that if one neglects these aspects, as would be the case in a mean-variance allocation, a significant cost would arise. The performance...

This paper focuses on the many extreme credit default swap spread movements observed during the recent credit crisis and on how the tails of the spread (and price) change distribution significantly differ from those of the normal distribution even for diversified credit derivatives portfolios....

Objective Bayesian inference procedures are derived for the parameters of the multivariate random effects model generalized to elliptically contoured distributions. The posterior for the overall mean vector and the between-study covariance matrix is deduced by assigning two noninformative priors...