the Efficient Method of Moments implemented to estimatestochastic volatility models this will surely be the case … method of momentstechnique for a broad range of univariate stochastic volatility models. As a side effect of the … volatility models. It describes the program. Some examples are given from other workof the author. Technicalities are given in …

conditional variance is modelled by a stochastic volatility process. We develop a Monte Carlo maximum likelihood method to obtain … variance, in the order of integration, in the short memory characteristics and in the volatility of volatility. …

When analysing the volatility related to high frequency financial data, mostly non-parametric approaches based on … stochastic volatility. Estimation of the model delivers measures of daily variation outperforming their non …

accounts for time variation in macroeconomic volatility, known as the great moderation. In particular, we consider an … volatility processes and mixture distributions for the irregular components and the common cycle disturbances enable us to … that time-varying volatility is only present in the a selection of idiosyncratic components while the coefficients driving …

volatility processes. This is called a GSSF-SV model. We show that conventional MCMC algorithms for this type of model are …

In this paper we aim to measure actual volatility within a model-based framework using high-frequency data. In the … at smaller and smaller time intervals. High-frequency returns are used for the computation of realised volatility. Recent … theoretical results have shown that realised volatility is a consistent estimator of actual volatility but when it is subject to …