This paper explains how the Gibbs sampler can be used to perform Bayesian inference on GARCH models. Although the Gibbs sampler is usually based on the analytical knowledge of the full conditional posterior densities, such knowledge is not available in regression models with GARCH errors. We...

This paper considers the Bayesian analysis of threshold regression models. It shows that this analysis can be conducted with simple deterministic numerical integration rules of low dimension. The shape of the posterior density is greatly determined by the type of threshold and of transition...

This paper shows how one can compute option prices from a Bayesian inference view point, using a GARCH model for the dynamics of the the volatility of the underlying asset. The proposed evaluation of an option is the predictive expectation of its payoff function. The predictive distribution of...

This paper proposes a new kind of asymmetric GARCh where the conditional variance obeys two different regimes with a smooth transition function. In one formulation variance reacts differently to negative and positive shocks while a second formulation, small and big shocks have separate effects.

This paper considers the Bayesian analysis of threshold regression models. It shows that this analysis can be conducted with simple deterministic numerical integration in one or two dimensions. The shape of the posterior density is greatly determined by the type of threshold and of transition...

This paper evaluates the latest version 4.4 of the econometric software TSP. After reviewing the general estimation methods, the originalities of the software are underlined, compared to what is available on the market. Some aspects of programming in TSP are detailed and th enew Window 95...