run. Thus, the estimation period shows that with increasing forecasting horizon predictability of simple real returns of …

estimation windows. It develops theoretical results for random walks when their drift and/or volatility are subject to one or …This paper considers forecast averaging when the same model is used but estimation is carried out over different … more structural breaks. It is shown that compared to using forecasts based on a single estimation window, averaging over …

Most of the empirical applications of the stochatic volatility (SV) model are based on the assumption that the … conditional distribution of returns given the latent volatility process is normal. In this paper the SV model based on a … choice of the conditional distribution has systematic effects on the parameter estimates of the volatility process. …

solved by considering heteroscedasticity of the structural volatility innovations, and estimation takes place in an …Information flows across international financial markets typically occur within hours, making volatility spillover … appear contemporaneous in daily data. Such simultaneous transmission of variances is featured by the stochastic volatility …

We consider a stochastic volatility model of the mean-reverting type to describe the evolution of a firm’s values … default probability. Our simulation results indicate that the stochastic volatility model tends to predict higher default … probabilities than the corresponding Merton model if a firm’s credit quality is not too low. Otherwise the stochastic volatility …

Estimation of the volatility of time series has taken off since the introduction of the GARCH and stochastic volatility … unobserved stochastic volatility, and the varying approaches that have been taken for such estimation. In order to simplify the … comprehension of these estimation methods, the main methods for estimating stochastic volatility are discussed, with focus on their …