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Risk-Based Selection of Portfolio: Heuristic Approach
Abstract
This chapter examines the closeness between the optimum portfolio and portfolio selected by an investor who follows a heuristic approach. There may be basically two ways of arriving at an optimum portfolio – one by minimizing the risk and the other by maximizing the return. In this chapter, the authors propose to strike a balance between these two. The optimum portfolio has been obtained through a mathematical programming framework so as to minimize the portfolio risk subject to return constraint expressed in terms of coefficient of optimism (a), where a varies between 0 to 1. Simultaneously, the authors propose to develop four heuristic portfolios for the optimistic and pessimistic investors, risk planners, and random selectors. Given the optimum portfolio and a heuristic portfolio, City Block Distance has been calculated to measure the departure of the heuristic solution from the optimum solution. Based on daily security wise data of ten companies listed in Nifty for the years 2004 to 2008, the authors have obtained that when the value of a lies between 0 to 0.5, the pessimistic investor's decision is mostly closest to the optimum solution, and when the value of a is greater than 0.5, the optimistic investor's decision is mostly near to the optimum decision. Near the point a = 0.5, the random selectors and risk planners' solutions come closer to the optimum decision. This study may help the investors to take heuristic investment decision and, based on his/her value system, reach near to the optimum solution.
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