Performance Evaluation of Genetic Algorithm & Fuzzy Logic for Portfolio Optimization

Abstract

Teaching-learning based optimization (TLBO), biogeography-based optimization (BBO) and fuzzy multi-objective linear programming (FMOLP) are compared in this paper for portfolio optimization. A hybrid approach has been adopted for this comparative study which is a combination of a few methods, such as investor topology, cluster analysis, analytical hierarchy process (AHP) and optimization techniques. Return, risk, liquidity, coefficient of variation (CV) and AHP weighted scores are used as the objective function for optimization.