In this article we show how bias approximations for the quasi maximum likelihood estimators of the parameters in Generalized Autoregressive Conditional Heteroskedastic (GARCH)(p, q) models change when any number of exogenous variables are included in the mean equation. The approximate biases are...

In this paper we provide simulation and theoretical results concerning the finite sample theory of QML estimators in ARCH models when we include an exogenous variable in the conditional variance equation. In this setting, we find theoretical and simulation support to suggest that if we consider...

This article considers the modelling of short-term interest rates with the ARFIMA model in six European countries based on daily data in the 1990s using the Modified Profile Likelihood estimation method. This allows one to study the different convergence processes that have been followed in each...

One unresolved issue arising from the use of eminent domain power involves how the perceived benefits and costs of eminent domain power affect people’s positions on the reform of eminent domain and police power law. The paper addresses this issue by estimating a voting model that explains...

This paper reconsiders a block bootstrap procedure for Quasi Maximum Likelihood estimation of GARCH models, based on the resampling of the likelihood function, as proposed by Goncalves and White [2004. Maximum likelihood and the bootstrap for nonlinear dynamic models. journal of Econometrics...

A new semiparametric estimator for an empirical asset pricing model with general nonparametric risk-return tradeoff and a GARCH process for the underlying volatility is introduced. The estimator does not rely on any initial parametric estimator of the conditional mean function, and this feature...

We have analysed extreme movements of the main stocks traded in the Eurozone by sectors in the 2000's decade. We find several patterns. <italic>First</italic>, we can classify firms by sector according to their different estimated Value-at-Risk (VaR) values but we cannot find differences according to their...