Portfolio Optimization Using Markowitz s Mean-Semi Variance Method on Tehran Stock Exchange

This paper presents an alternative to the standard mean-variance efficient frontier model underpinning modern portfolio theory applications. We present a more practical alternative - A Mean Semivariance efficient frontier - that takes into consideration advances in “Post Modern Portfolio Theory” as it pertains to asset allocation. The implications for advisors and planners are profound: An investor’s minimal acceptable return is a critical determinant of their optimal portfolio; Efficient frontiers need not be continuous, reflecting the realities of market behavior and demonstrated volatility; This new method for calculating frontiers is a preferred device for developing strategic asset allocations. What is so efficient about the “efficient frontier?” The Markowitz (1952) model is employed to determine the optimal mix of risky securities. This methodology involves determining what the minimum risk combination of securities or asset classes is for a given return. Risk, in this context, is defined as the standard deviation of returns of a composite portfolio. By plotting these risk-return combinations, an “efficient frontier” is generated (with the “efficient” part being the upper boundary). Is this really the preferred way to look at risk and use it in portfolio selection? If it is not, then is this frontier really “efficient?” In this paper we have modified the traditional Markowitz paradigm by redefining risk. The definition of risk we employ in this paper is “Semi-Standard Deviation” instead of “Standard Deviation”. Then we have constructed efficient frontier for top fifty securities of Tehran stock exchange using Downside Risk approach or “Mean-Semivariance” method. In this research we achieved more efficient frontier using this method than the traditional one.