In this paper, we review the most common specifications of discrete-time stochastic volatility (SV) models and illustrate the major principles of corresponding Markov Chain Monte Carlo (MCMC) based statistical inference. We provide a hands-on ap proach which is easily implemented in empirical...

This paper examines the hypothesis that both stock returns and volatility are asymmetric functions of past information derived from domestic and U.S. stock-market news. The results show the presence of negative autocorrelation, which is consistent with the dominance of positive-feedback trading...

The paper proposes a new robust estimator for GARCH-type models: the nonlinear iterative least squares (NL-ILS). This estimator is especially useful on specifications where errors have some degree of dependence over time (weak-GARCH) or when the conditional variance is misspecified. I illustrate...

We consider the properties of three estimation methods for integrated volatility, i.e. realized volatility, the Fourier estimator, and the wavelet estimator, when a typical sample of high-frequency data is observed. We employ several different generating mechanisms for the instantaneous...

In this research paper ARCH-type models are applied in order to estimate the Value-at-Risk (VaR) of an inflation-index futures portfolio for several time-horizons. The empirical analysis is carried out for Mexican inflation-indexed futures traded at the Mexican Derivatives Exchange (MEXDER). To...

Econometric estimation using simulation techniques, such as the efficient method of moments, may betime consuming. The use of ordinary matrix programming languages such as Gauss, Matlab, Ox or S-plus will very often cause extra delay. For the Efficient Method of Moments implemented to...

Tests for structural stability with unknown breakpoint are derived for and applied tothe efficient method of moments. Three types of tests are discerned: Wald type tests,Predictive tests and Hansen type tests. The Hansen type test for structural stabilitywith unknown breakpoint is a novelty for...

Daily returns of financial assets are frequently found to exhibit positive autocorrelation at lag 1. When specifying a linear AR(l) conditional mean, one may ask how this predictability affects option prices. We investigate the dependence of option prices on autoregressive dynamics under...

We introduce a new efficient importance sampler for nonlinear non-Gaussian state space models. We propose a general and efficient likelihood evaluation method for this class of models via the combination of numerical and Monte Carlo integration methods. Our methodology explores the idea that...

A large number of nonlinear conditional heteroskedastic models have been proposed in the literature. Model selection is crucial to any statistical data analysis. In this article, we investigate whether the most commonly used selection criteria lead to choice of the right specification in a...