obtained from discrete time models by comparing them with high-frequency ex post estimates (e.g. realised volatility) based on … continuous time theory. In explanatory financial variability modelling this raises several methodological and practical issues … properties of operational and practical procedures for the forecast evaluation of explanatory discrete time models of financial …

investment horizons. This change in behavior leads to less volatility and less mispricings. When the tax rate exceeds a certain …

We investigate the marginal predictive content of small versus large jump variation, when forecasting one …. Investors prefer stocks with a high probability of having positive jumps, but they also tend to overweight safer industries …, even when controlling for these variables. By analyzing earnings announcement surprises, we find that large jumps are …

The capacity of input-output tables to reflect the structural peculiarities of an economy and to forecast, on this …

of them forecasting future mortality rates by extrapolating one or more latent factors. The abundance of proposed models … shows that forecasting future mortality from historical trends is non-trivial. Following the idea proposed in Deprez et al … learning estimator is then forecasted according to the Lee-Carter framework, allowing one to obtain a higher forecasting …

volatility. …