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 …

subject to stochastic volatility. It enables the disentanglement of dynamic structures in both the mean and the variance of … increased during the 2008 financial crisis while it has recently returned to its pre-crisis level. The extracted volatility …

We investigate high-frequency volatility models for analyzing intra-day tick by tick stock price changes using Bayesian … estimation procedures. Our key interest is the extraction of intra-day volatility patterns from high-frequency integer price … distributions. We allow for stochastic volatility by modeling the variance as a stochastic function of time, with intra-day periodic …

Estimation of the volatility of time series has taken off since the introduction of the GARCH and stochastic volatility … models. While variants of the GARCH model are applied in scores of articles, use of the stochastic volatility model is less … unobserved stochastic volatility, and the varying approaches that have been taken for such estimation.In order to simplify the …