Robust optimization framework for cardinality constrained portfolio problem

One of the primary concerns on any asset allocation problem is to maintain a limited number of assets from the market. The problem becomes more complicated when the return of all risky assets are subject to uncertainty. In this paper, we propose a new portfolio modeling approach with uncertain data and it is also analyzed using different robust optimization techniques. The proposed formulations are solved using genetic algorithm. The implementation of the proposed method is examined on variety of well known benchmark data sets.

► New portfolio problem formulation under uncertainty. ► Applying different robust optimization technique to solve an uncertain LP and compare them using a real data set. ► Incorporating cardinality constraint together with short selling for portfolio problem. ► Developing a standard GA to solve resulted MILP.