The EGARCH is a popular model for discrete time volatility since it allows for asymmetric effects and naturally ensures positivity even when including exogenous variables. Estimation and inference is usually done via maximum likelihood. Although some progress has been made recently, a complete...

This paper proposes an extension of the standard one-way error components model allowing for heteroscedasticity in both the individual-specific and the general error terms, as well as for unbalanced panel. Onthe grounds of its robustness to distributional misspecification, its robustness to...

The paper deals with the power and robustness of the R/S type tests under contiguous alternatives. We briefly review the long memory models in levels and volatility, and describe the R/S-type tests used to test for the presence of long memory. The empirical power of the tests is investigated...

We propose and study by means of simulations and graphical tools a class of goodness-of-fit tests for ARCH models. The tests are based on the empirical distribution function of squared residuals and smooth (parametric) bootstrap. We examine empirical size and power by means of a simulation...

We consider a class of microeconomic models with interacting agents which replicate the main properties of asset prices time series: nonlinearities i levels and common degree of long-memory in the volatilities and co-volatilities of multivariate time series. For these models, longrange...

Two classes of tests designed to detect changes in volatility are proposed. Procedures based on squared model residuals and on the likelihood ratio are considered. The tests are applicable to parametric nonlinear models like GARCH. Both asymptotic and bootstrap tests are investigated by means of...

This paper proposes a convenient and generally applicable diognostic m-test for checking the distributional specification of parametric conditional heteroscedasticity models for financial data such as customary student t GARCH model. The proposed test is based on the moments of probability...

This paper considers GMM estimation of autoregressive processes. It is shown that, contrary to the case where the noise is independent, using high-order moments can provide subtantial efficiency gains for estimating the AR model when the noise is only uncorrelated.

This paper considers GMM estimation of autoregressive processes. It is shown that, contrary to the case where the noise is independent (see Kim, Qian and Schmidt (1999)), using high-order moments can provide substantial efficiency gains for estimating the AR(p) model when the noise is only...

This paper deals with the impact of nine categories of scheduled and unscheduled news announcements on the Euro/Dollar return volatility. We highlight and analyze the pre-announcement, contemporaneous and postannouncement reactions. Using high-frequency intraday data and within the framework of...