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The Markowitz issue of optimization can’t be solved by precise mathematical methods such as second order schematization, when real world condition and limitations are considered. On the other hand, most managers prefer to manage a small Portfolio of available assets in place of a huge Portfolio. It can be analogized to cardinal constrains, that is, constrains related to minimum and maximum current assets on Portfolios. This study aims to solve the problem of optimizing Portfolios with cardinality constrains, using simulated annealing algorithm. Therefore, by using the information of 50 companies which have been more active in Tehran’s exchange stock from April 2010 to April 2012, Portfolios’ efficient frontier has been supposed from 10 to 50. Results shows that first, simulated annealing algorithm has been successful in solving the above problem, and second, by selecting shares appropriately and determining suitable weights from it, smaller Portfolios with more suitable performances can be selected.

Short-selling prohibition has been one of the primary assumptions of Markowitz mean-variance model. Solving Markowitz quadratic model creates investment efficient frontier by considering only two return and budget constraints. In order to develop a more realistic portfolio selection model, in this paper, a new mathematical model is developed to allow short-selling under some practical constraints. Non-linear model offered is maped by using solved standard tools and constrained efficient frontier with using from 15 shares price information.

In this paper with the aims to examine the changes in productivity, two well-known techniques of evaluation over time studied that window Analysis and Malmquist productivity index and by selecting the appropriate length for the windows, the window Analysis and a newer version of Malmquist productivity index used within compilation framework implemented so that performance compared to the same period in consecutive time, and adding new information to does not lead the necessity of repeating the previous calculations periods. In this framework, we combine the two techniques in an attempt to compensate for the weaknesses of each to help with the implementation of a simple statistical test; the overall situation information is also frontiers of technology. Shifted of techniques that have steadily organized manner at any point of use with minimal calculations relatively comprehensive level of information provided. Proposed Framework for Supervision Bureau of the Sepah Bank South of Tehran in 9 Periods of has been applied to the detection of four cases of shift frontier, the performance of the proposed framework is shown to be the case.

For the first time, this paper analyzes the portfolio selection theory in the presence of housing market in Iran. One of the important theories about the housing price is household portfolio theory. Based on the theory, housing business cycles have determining effect on housing share in portfolio. For this purpose, a set of assets data consisting stocks, exchange, gold coins, bank deposits, bonds and housing over the period 1991-2006 are used. After calculation of returns, risks and correlation coefficients of assets over the period using Mean - Variance Model and MATLAB software, a combination of household assets in the portfolio have been extracted .The model, through simulating and supposing different weights for each asset determines an optimal combination of assets in portfolio based on risk classification of households: low risk, medium risk and high risk. Then, they are thoroughly examined to explore: whether the presence of housing asset in the portfolio can improve its risk, return and the composition of assets? Efficient frontier which covers all portfolios is also extracted. The results reveal that housing is an important asset in the portfolio during the housing boom period and causes the efficient frontier transmission move outwards.

The focus of this paper is on standard Markowitz mean–variance model and its traditional approach to solve portfolio selection problem (Quadratic Planning). For this goal we have applied a meta-heuristic method based on genetic algorithms (GA) in order to trace out the efficient frontier associated with the portfolio selection problem under cardinality and bounding constraints. These constraints ensure the investment in a given number of different assets and limit the amount of capital to be invested in each asset. We have presented some experimental results in two samples from Iranian stock market and overseas ones and compare the GA result with unconstrained quadratic results. Finally, we have found out which proposed GA can optimize portfolio selection problem under cardinality and bounded constrains

In this paper we study one of the most important challenges facing the Iranian Oil authorities: The allocation of natural gas reserves to different uses like exports, petrochemical plants, and injection to oil reserves for enhancing recovery factor. The results show that in the ranking of the project groups on the basis of expected net present value and risk index, the export projects group has a greater value and risk than gas injection projects group and petrochemical group. In choosing the portfolios on the efficient frontier, the amount of gas allocated to export projects should be less if we aim the lower risk than the situation with higher values and risk. However, the amount of gas allocated to injection and petrochemical projects groups will decrease as the risk and value of portfolios increase. Also, the results show that the more risk lover the investor, the higher the amount of gas allocated to gas export projects group.