In this paper we propose a new method to specify linear models for vectors of time series with some convenient properties: First, it provides a unique modeling approach for single and multiple time series, as the same decisions are required in both cases. Second, it is scalable, meaning that it...

This paper analyzes the unconditional measurement of default risk and proposes an alternative modeling approach. We begin the analysis by showing that when conducted under non-stationarity, the objective of the unconditional measurement changes and that some relevant problems appear as a...

A seller sets up an advertising policy so as to maximize a flow of discounted utility over time in a scenario characterized by two essential issues. First, the seller is ignorant from the outset of the prospective customers' willingness to buy and runs a Bayesian learning process in parallel to...

This paper tackles the mixed-frequency modeling problem from a new perspective. Instead of drawing upon the common distributed lag polynomial model, we use a transfer function representation to develop a new type of models, named TF-MIDAS. We derive the theoretical TF-MIDAS implied by the...