, stochastic volatility coupled with fat tails, GARCH and mixture of innovation models. The comparison is based on the accuracy of … volatility specifications, in terms of point forecasting to some degree and density forecasting to a greater degree. …

We present an estimation and forecasting method, based on a differential evolution MCMC method, for inference in GARCH … nearly all series. Finally, we carry out a forecasting exercise to evaluate the usefulness of structural break models. …

We develop efficient simulation techniques for Bayesian inference on switching GARCH models. Our contribution to … space models with particular attention to MS-GARCH models. Our multi-move sampling strategy is based on the Forward … Filtering Backward Sampling (FFBS) applied to an approximation of MS-GARCH. Another important contribution is the use of multi …

-known GARCH models for density prediction of daily S&P 500 and Nikkei 225 index returns, a comparison is provided between …

Small or medium-scale VARs are commonly used in applied macroeconomics for forecasting and evaluating the shock … forecasting context. While none of the methods clearly emerges as best, some techniques turn out to be useful to improve the … forecasting performance. …

sudden shifts in the level of volatility. In an out-of-sample forecasting application we show that the BVAR model with …