Portfolio optimization using sharpe ratio with particle swarm optimization algorithm

Abstract

Portfolio Optimization is the process to select the best portfolio out of all the available portfolios according to some objective. It is a very interesting as well as important field of the financial sciences. In this report we are using a meta-heuristic algorithm named Particle Swarm Optimization (PSO) to find a portfolio with maximum Sharpe ratio. The sharpe ratio is simple and it is a risk adjusted measure of return that is used to evaluate the performance of a portfolio. Particle Swarm Optimization (PSO) is a population based stochastic optimization technique developed by Kennedy and Eberhart in 1995, inspired by social behavior of bird flocking. This report uses PSO to solve portfolio optimization problems and we will compare the results of PSO to that of Genetic Algorithm.