Particle Swarm Optimisation Approach in the Construction of Optimal Risky Portfolios

Abstract

In this paper, we apply particle swarm optimisation to the construction of optimal risky portfolios for financial investments. Constructing an optimal risky portfolio is a high-dimensional constrained optimisation problem where financial investors look for an optimal combination of their investments among different financial assets with the aim of achieving a maximum reward-to-variability ratio. A particle swarm solver is developed and tested on various restricted and unrestricted risky investment portfolios. The particle swarm solver demonstrates high computational efficiency in constructing optimal risky portfolios of less than fifteen assets. The effectiveness of a weighting function in the particle swarm optimisation algorithm is also studied.