simulation evidence for stochastic volatility and stochastic intensity models. For our empirical study, we analyse the …

orhistorical and Monte Carlo simulation methods. Although these approaches to overall VaR estimation have receivedsubstantial … the underlying statistical distributions, a variety of analyticalmethods and simulation-based methods are available. Aside … and incremental VaR in either a non-normal analytical setting or a MonteCarlo / historical simulation context.This paper …

We study the performance of two analytical methods and one simulation method for computing in-sample confidence bounds …. They are applicable to the complete class of observation driven models and are valid for a wide range of estimation … provided by our three methods of computing in-sample bounds. The analytical methods may be less reliable than the simulation …

). Simulation evidence indicatesthe practical relevance of the method. It is illustrated on quarterly post-war USindustrial …

This note presents the R package bayesGARCH (Ardia, 2007) which provides functions for the Bayesian estimation of the … parsimonious and effective GARCH(1,1) model with Student-<I>t</I> innovations. The estimation procedure is fully automatic and thus …

estimation of the tail of the predictive distribution. Two novel concepts are introduced that offer a specific focus on this part …

estimation strategies available for the Bayesian inference of GARCH-type models. The emphasis is put on a novel efficient … the posterior density of the model parameters. This density is then used in importance sampling for model estimation …