This paper provides the theoretical and operational framework for estimating past values of relevant time series starting from a (limited) information set. We consider a general approach that includes as special cases time series aggregation and temporal and/or spatial disaggregation problems....

This work deals with multivariate stochastic volatility models, which account for a time-varying variance-covariance structure of the observable variables. We focus on a special class of models recently proposed in the literature and assume that the covariance matrix is a latent variable which...

The condition of Risk Aversion implies that the Utility Function must be concave. Taking into account the dependence of the Utility Function on the wealth that in turn depends on the return, we consider a return with any type of two-parameter distribution. It is possible to define Risk and...

This paper analyzes the dependence of the Certainty Equivalent Return of a Constant Relative Risk Aversion, CER[CRRA], on the Standard Deviation of the Return with the hypothesis of a Truncated Normal distribution of returns and for some level of Relative Risk Aversion (RRA) parameter. The paper...

Factor models (FM) are now widely used for forecasting with large set of time series. Another class of models, which can be easily estimated and used in a large dimensional setting, is multivariate autoregressive models (MAR), where independent autoregressive processes are assumed for the series...

The condition of Risk Aversion implies that the Utility Function must be concave. We take into account the dependence of the Utility Function on the return that has any type of two-parameter distribution; it is possible to define Risk and Target, the former may be the Standard Deviation of the...