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 …

subject to stochastic volatility. It enables the disentanglement of dynamic structures in both the mean and the variance of … the observed time series. We develop a simulated maximum likelihood estimation method based on importance sampling and … increased during the 2008 financial crisis while it has recently returned to its pre-crisis level. The extracted volatility …

This paper considers spot variance path estimation from datasets of intraday high frequency asset prices in the … microstructure noise has an adverse effect on both spot variance estimation and jump detection. In our approach we can analyze high …

subject to stochastic volatility. It enables the disentanglement of dynamic structures in both the mean and the variance of … the observed time series. We develop a simulated maximum likelihood estimation method based on importance sampling and … increased during the 2008 financial crisis while it has recently returned to its pre-crisis level. The extracted volatility …

Although the main interest in the modelling of electricity prices is often on volatility aspects, we argue that … towards volatility features of the time series.For the older electricity market of Nord Pool in Norway, it is found that a …