Volatility permeates modern financial theories and decision making processes. As such, accurate measures and good … forecasts of future volatility are critical for the implementation and evaluation of asset pricing theories. In response to this …, a voluminous literature has emerged for modeling the temporal dependencies in financial market volatility at the daily …

multiple stochastic volatility processes. The estimation is based on annual consumption data from 1929 to 1959, monthly … are omitted from the estimation). Three independent volatility processes capture different frequency dynamics; our … predictable component and use high-frequency data, whenever available, to efficiently identify the volatility processes. Our …

, including the average equity premium and the volatility of equity returns. We construct a model with RE (temporary and permanent … parts) and LRR (including stochastic volatility) and estimate this model with long-term data on aggregate consumption for 42 … economies. RE typically associates with major historical episodes, such as the world wars and the Great Depression and analogous …

structure to commodity futures prices, and develop new algorithms for estimation of such models using unbalanced data sets in …

We compare the out-of-sample forecasting performance of univariate homoskedastic, GARCH, autoregressive and …