For a class of parametric ARCH models, Whittle estimation based on squared observations is shown to be inconsistent and asymptotically normal. Our conditions require the squares to have short memory autocorrelation, by comparison with the work of Zaffaroni (1999), who established the same...

For a class of long memory volatility models, we establish the asymptotic distribution theory of the Gaussian estimator and the Lagrange multiplier test. Both the case of estimation of martingale difference and ARMA levels are considered. A Montecarlo exercise is presented to assess the small...

Estimation methods of bivariate fractional cointegration models are numerous. In most cases they have non-equivalent asymptotic and finite sample properties, implying diffculties in determining an optimal estimation strategy. In this paper, we address this issue by means of simulations and...

Academics and practitioners have extensively studied Value-at-Risk (VaR) to propose a unique risk management technique that generates accurate VaR estimations for long and short trading positions and for all types of financial assets. However, they have not succeeded yet as the testing...

The uncertainty plays a central role in most of the problems which addressed by the modern financial theory. For some time, we know that the uncertainty under the speculative price varies over the time. However, it is only recently that a lot of studies in applied finance and monetary economics...

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...

The objective of this paper is to analyze and analytically quantify the effect of additive outliers in the forecasting of volatility from an ARCH Model. For it, we start by distinguishing between Additive Level Outliers (ALO) and Additive Volatility Outliers (AVO), obtaining the analytical...

En este trabajo se presenta la metodología bootstrap como una alternativa para construir intervalos de predicción en series temporales cuando las hipótesis usuales de los métodos clásicos no son sostenidas por los datos, o cuando el tamaño muestral no es suficientemente elevado para...

En el presente trabajo se introduce al lector en los modelos autorregresivos para la varianza condicionada heterocedástica, incidiendo en los problemas que plantean los esquemas más sencillo y sugiriendo diversas soluciones. Se describe el concepto, las hipótesis y los modelos que explican la...

The asymptotic distribution of a vector of autocorrelations of squared residuals is derived for a wide class of asymmetric GARCH models. Portmanteau adequacy tests are deduced. %gathered These results are obtained under moment assumptions on the iid process, but fat tails are allowed for the...