Robust Portfolio Asset Allocation: models and algorithmic approaches

Many financial optimization problems involve future values of
security prices, interest rates and exchange rates which are not
known in advance, but can only be forecasted or estimated. Such
problems fit perfectly into the framework of Robust Optimization
that, given optimization problems with uncertain parameters, looks
for solutions that will achieve good objective function values for
the realization of these parameters in given uncertainty sets.
In finance, Robust Optimization offers vehicles to incorporate
the estimation of uncertain parameters into the decision making process.
This is true, for example, in portfolio asset allocation. Starting from the robust counterparts of the classical mean-variance portfolio  problems,
in this paper we review some mathematical models that have been recently proposed in the literature to address uncertainty in portfolio asset allocation problems.
For some of these, we focus also on algorithmic approaches and computataional issues. Finally, we analyze the relationship between robustness and risk measures.