Applications of Multi-Objective Evolutionary Algorithms in Modeling of Higher Order Portfolio Selection Problems

Financial portfolio formation is usually a multiobjective
decision-making problem concerning return and risk on the investment.
When the returns are asymmetrical, a portfolio with higher skewness
becomes desirable since it is predicted to deliver higher future
returns. This motivates the formulation of portfolio optimization models
in various environments with higher moments and practical constraints. A
metaheuristic procedure is required to solve the higher-moments
portfolio selection models involving conflicting objectives and
realistic constraints. Further, the model is validated on the real stock
market data for determining its future performance.