We solve two robust portfolio selection problems, where a maxmin criterion is adopted to deal with parameter uncertainty. The two models, which yield closed formulae for the optimal allocation, lend themselves to be thoroughly analyzed both from a geometric and a game-theoretic point of view.

A time series model in which the signal is buried in non-Gaussian noise may throw up observations that are outliers when judged by the Gaussian yardstick. We describe an observation-driven model, based on an exponential generalized beta distribution of the second kind (EGB2), in which the signal...

We compare two EGARCH models, which belong to a new class of models in which the dynamics are driven by the score of the conditional distribution of the observations. Models of this kind are called dynamic conditional score (DCS) models and their form facilitates the development of a...