Value-at-Risk Based Portfolio Allocation Using Particle Swarm Optimization

Authors

  • Ray J Department of Science and Humanities RCC Institute of Information Technology Canal South Road, Beliaghata Kolkata – 700 015, India
  • Bhattacharyya S Department of Information Technology RCC Institute of Information Technology Canal South Road, Beliaghata Kolkata – 700 015, India

Keywords:

Portfolio Management, Financial Instruments, Value-at-Risk, Particle Swarm Optimization

Abstract

Risks and returns are inevitably interlinked in today's work-a-day real world financial transactions. In particular, a financial portfolio illustrates the situation in which a combination of financial instruments/assets describes this interrelation in terms of their correlation in a particular market condition. The field of portfolio management has assumed importance of late, thanks to the need for decision making in investment opportunities in a high-risk scenario. It addresses the risk-reward tradeoff allocation of investments to a number of different assets so as to maximize returns or minimize risks in a given investment period. In this paper, a particle swarm optimization procedure is used to evolve optimized portfolio asset allocations in a volatile market condition. The proposed approach is centered around optimizing the Value-at-Risk (VaR) measure in different market conditions based on several objectives and constraints. Applications of the proposed approach are demonstrated on a collection of several financial instruments.

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Published

2015-02-28

How to Cite

[1]
J. Ray and S. Bhattacharyya, “Value-at-Risk Based Portfolio Allocation Using Particle Swarm Optimization”, Int. J. Comp. Sci. Eng., vol. 3, no. 1, pp. 1–9, Feb. 2015.

Issue

Vol. 3 No. 1 (2015): IJCSE Special Issue February Edition

Section

Research Article

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