| Summary: | The formation of the optimum portfolio based on risk and return is one of the most important decisions of investors in financial markets, for which there are various methods. Markowitz’s Mean-Variance method was the first method introduced in this area; but because of the normality assumption for the return distribution function, it only considered specific characteristics (expected return and variance) of the return distribution function. Another method introduced years later was the Stochastic Dominance method which considers all of the return distribution function instead of specific characteristics such as variance. The present research investigates the “Stochastic Dominance method” in portfolio optimization and compares the performance of this method with “Markowitz Portfolio Optimization method” using performance evaluation criteria in the Tehran Stock Exchange. The performance evaluation criteria used in this article are: Sharpe, Treynor, Sortino and Omega. The results of this research indicate the advantage of Second Order Stochastic Dominance method on the Markowitz method in out-of-sample and in-sample approaches. Moreover the Second Order Stochastic Dominance method has a higher cumulative return than the Markowitz method.
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