Abbas Rezaei Pandari; Adel Azar; Alireza Rayati Shavazi
Volume 16, Issue 48 , October 2011, , Pages 109-134
Abstract
Generally, investors consider simultaneously conflicting objectives such as rate of return, risk and liquidity in portfolio selection. On the other hand, every investor has his own specific preferences about objectives. Therefore, we can use Multi Objective Decion Making (MODM) techniques in order to ...
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Generally, investors consider simultaneously conflicting objectives such as rate of return, risk and liquidity in portfolio selection. On the other hand, every investor has his own specific preferences about objectives. Therefore, we can use Multi Objective Decion Making (MODM) techniques in order to solve portfolio selection problem. The Studies shows that a MODM technique by nonlinear goals such as minimization of nonsystematic risk and skewness maximization isn’t employed for portfolio selection, so a new approach is applied. We employ MODM model to select a best portfolio in 50 superior companies in Tehran stock exchange with regards to optimization objectives of return, systematic risk, nonsystematic risk, skewness, liquidity and sharp ratio. This model is non-convexed, so operational research algorithms can not find the best solution; therefore we use Genetic Algorithms (GA) for achieving nonlinear multi-objective model. In the end, the result of GA is comprised with Markwitz classic model and goal programming (containing linear and nonlinear objectives). The comparison indicates that although return of the portfolio of GA model is less than the other models, but GA has the best results in decreasing risk criteria which completely cover the return and lead to best results. The other advantage of using GA is a higher diversification in its proposed portfolio in comparison with other models.
Simin Abdolalizadeh Shahir; Koroush Eshghi
Volume 5, Issue 17 , February 2004, , Pages 175-192
Abstract
One of the classical applications of operation research in investment decision making is the portfolio selection problem. In this problem a fixed sum of money is to be spread among different investments and there is a risk associated with the rate of return on each investment. The object of the portfolio ...
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One of the classical applications of operation research in investment decision making is the portfolio selection problem. In this problem a fixed sum of money is to be spread among different investments and there is a risk associated with the rate of return on each investment. The object of the portfolio selection problem is to determine how much money should be allocated to each investment to maximize the total expected return and minimize the portfolio’s risk. Since there is no specific algorithm to find an optimal feasible solution for large scale portfolio problems, in this paper two genetic algorithms are developed to find a near optimal solution. In the first algorithm the selection of investments is determined and in the second one the weight of each investment in the portfolio is calculated. Finally, the two algorithms have been applied successfully to the portfolio of stocks of the Tehran Stock Exchange with more than 200 stocks.