Hossein Marzban; Ali Hossein Ostadzad
Abstract
Ongoing sanctions on Iranian economy have proved to be very harmful and detrimental to Iranian economic affairs and social welfare. Evaluating the unfair impacts of these sanctions on Gross Domestic Product (GDP) and social welfare is the aim of this paper. Firstly, we have developed a generalized growth ...
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Ongoing sanctions on Iranian economy have proved to be very harmful and detrimental to Iranian economic affairs and social welfare. Evaluating the unfair impacts of these sanctions on Gross Domestic Product (GDP) and social welfare is the aim of this paper. Firstly, we have developed a generalized growth model in the presence of sanctions while treating exchange rate as a random variable. Secondly, three different forms of sanctions are introduced into the model and their bearings on national product and social welfare is studied. The first tier of the sanctions is imposed on consumption, intermediary and capital goods while exchange rate is assumed to have a random behavior. Then sanctions are also imposed on Iranian oil and gas production. We have devised several scenarios using stochastic Hamilton Bellman Jacobian value function (SHBJ) and genetic algorithm optimization methods. Our results of the first and second scenario imply that the level of social welfare is mostly affected by oil and gas sanctions while goods embargo has targeted goods production. The effects of sanctions on GDP and social welfare is represented by a concave curve. This curvature shows that the impact of sanctions on GDP and social welfare is stronger at the beginning than later on when further sanctions are introduced. In the third scenario oil, gas and goods sanctions are imposed simultaneously. Our results also show that the third scenario effects is stronger than the other two. According to the Gross Domestic Product data acquired for year 1390, oil and gas sanctions have lowered the GDP by 30 percent, while the overall reduction in GDP through all sanction collectively is estimated between 30 to 50 Percent.
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.
