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...

A unit root test is usually carried out by using the regression test introduced by Dickey and Fuller (1979). Under the null hypothesis the series should be a random walk. But a non-stationary series can usually be decomposed into a random walk and a stationary component. This is what is done in...

A unit root test is usually carried out by using the regression test introduced by Dickey and Fuller (1979). Under the null hypothesis the series should be a random walk and a stationary component. This is what is done in additive decompositions between trend and cycle. The paper analyses the...

In this paper we address the issue of the efficient estimation of the cointegrating vector in linear regression models with variables that follow general (higher order and fractionally) integrated processes.

In this paper we address the issue of the efficient estimation of the cointegrating vector in linear regression models with variables that follow general (higher order and fractionally) integrated processes.

In this paper we compare via Monte Carlo experiments some methods to estimate the parameter of long-range dependence. We then apply these procedures to a financial time series to investigate its long-memory properties. The evidence of smooth long-range dependence makes the usual Efficiency...

It is well known that when we have to do with possibly chaotic time series, it needs to reconstruct a pseudo state space. In this paper it has been studied, via simulations, a possible multivariate reconstruction and its effects on the one step prediction.

We consider truncated processes, both in discrete and continuous time, and study their dynamic properties. When the underlying process is a diffusion process, we derive the infinitesimal generator of its truncated counterpart. This result is the basis for the estimation of the drift and...

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...