MULTI-OBJECTIVE ASSET ALLOCATION APPROACH USING ANT COLONY OPTIMIZATION FOR PORTFOLIO MANAGEMENT

Abstract

Effective Portfolio allocation is a fundamental to financial management. To achieve maximum return while controlling risk, investors need to select the most suitable tools and techniques. Traditional portfolio optimization methods often rely on single-objective approaches, neglecting the importance of incorporating multiple objectives such as return, risk, and diversification. In this research paper, a multi-objective approach to Assets allocation using the Ant Colony Algorithm for optimization of mean variance model is proposed. This algorithm draws inspiration from the foraging behaviour of ants to effectively explore the solution space and provides assets allocations for optimal portfolios. The objective is to find an optimal balance between maximizing returns at targeted risks across different asset allocation options. The proposed approach offers a powerful tool for investors to make an automated informed decisions based on asset price movement in an uncertain financial market to readjust portfolio periodically to minimize risk and maximize return. ACO Forecasted portfolio return are compared with attained return, equal weightage portfolio return and NIFTY 50 Index return at every quarter.