A practice that has become widespread and widely endorsed is that of evaluating forecasts of financial variability 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...

A practice that has become widespread is that of comparing forecasts of financial return variability obtained from discrete time models against high frequency estimates based on continuous time theory. In explanatory financial return variability modelling this raises several methodological and...

A practice that has become widespread is that of comparing forecasts of financial return variability obtained from discrete time models against high frequency estimates based on continuous time theory. In explanatory financial return variability modelling this raises several methodological and...

The general-to-specific (GETS) approach to modelling is widely employed in the modelling of economic series, but less so in financial volatility modelling due to computational complexity when many explanatory variables are involved. This study proposes a simple way of avoiding this problem and...

We use data on the following climate variables for the period of the last 798 thousand years: global ice volume (Icet), atmospheric carbon dioxide level (CO2,t), and Antarctic land surface temperature (Tempt). Those variables are cyclical and are driven by the following strongly exogenous...

This paper identifies and estimates the relevant cycles in paleoclimate data of earth temperature, ice volume and CO2. Cyclical cointegration analysis is used to connect these cycles to the earth eccentricity and obliquity and to see that the earth surface temperature and ice volume are closely...