model for the autoregressive coefficient matrices and a multivariate dynamic volatility model for the variance matrix of the … and robustness of the method against potential misspecifications of the volatility in the disturbance vector. We further …

model for the autoregressive coefficient matrices and a multivariate dynamic volatility model for the variance matrix of the … and robustness of the method against potential misspecifications of the volatility in the disturbance vector. We further …

In this paper we present an exact maximum likelihood treatment forthe estimation of a Stochastic Volatility in Mean …(SVM) model based on Monte Carlo simulation methods. The SVM modelincorporates the unobserved volatility as anexplanatory variable … Stochastic Volatility (SV)model. However, efficient Monte Carlo simulationmethods for SV models have been developed to overcome …

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 …

improved volatility measurements but has also inspired research into their potential value as an information source for … volatility forecasting. In this paper we explore the forecasting value of historical volatility (extracted from daily return … series), of implied volatility (extracted from option pricing data) and of realised volatility (computed as the sum of …

improved ex-post volatility measurements but has also inspired research into their potential value as an informa-tion source … for longer horizon volatility forecasts. In this paper we explore the forecasting value of these high fre-quency series in … conjunction with a variety of volatility models for returns on the Standard & Poor's 100 stock index. We consider two so …

that is embedded in the time-varying parameter path. We illustrate our findings in a volatility analysis for monthly …