ROLE OF RETURN MAXIMISATION, RISK REDUCTION AND SHARE RETURN COVARIANCES IN MARKOWITZ PORTFOLIO EFFICIENCY

Abstract

One of the main challenges in portfolio management under Markowitz model is to determine the proportion of funds to be invested in each company’s share to optimize Sharpe ratio. It is all the more challenging when the portfolio size increases in terms of number of shares. Usually to tackle these problems the investors and fund managers will apply return or risk or by any other logical method. In this article we have used four techniques to optimize the Sharpe ratio. We select the shares based on their return variance and order them in ascending and descending orders. These variances are taken as the basis for allocating funds among the shares first in sequential order, then in ascending order, then in descending order and finally in random weights order. When funds are allocated in descending order of their variance, the portfolios produced maximum return with reasonable variance and maximized the Sharpe ratio. The random allocation of funds as suggested by Markowitz to get efficient frontier for identifying optimum weights is time consuming and requires a lot of number crunching. Our descending order allocation is quick and effective in maximizing return for small and medium sized portfolios. In larger portfolios the random allocation produces higher return with higher Sharpe ratios than the variance allocated portfolios. This is because, out of 1000 iterations, the maximum Sharpe ratios were extracted and presented for comparison. Our findings will benefit the small and medium size portfolios which will result in considerable savings in time and number crunching.