Optimization is a process of finding the best solution for a problem. Heuristic and metaheuristic optimization Algorithms are commonly used where the search space is complex. In recent decades, the ubiquity of trusses as structural systems has made their optimization an important engineering endeavor. The primary aim of structural optimization is to determine the most suitable combination of design variables, so as to achieve satisfactory performance of the structures subjected to constraints. the three basic features of the structural optimization problem are: The design variables, the objective function, the constraints. This study evaluates the performances of the Exchange Market Algorithm (EMA) in the structural optimization field for the first time. This optimization Algorithm is inspired by the procedure of trading the shares on stock Market. In the proposed method there are two different modes in EMA. In the first mode, there is no oscillation in the Market where as in the second mode, the Market has oscillation. For the first mode, the Algorithm’s duty is to recruit people toward successful individuals, while in the second case the Algorithm seeks optimal points. the member’s section area has assumed to be a decision variable, and the objective function is to minimize their weight. The member stresses and node displacements are the constraints that must maintain within the allowed limits for each condition. The implementation of Exchange Market Algorithm has been done in MATLAB software. to quantitatively assess the performance of the Algorithm, three planar trusses (10 bar, 18 bar, and 200 bar) and three space trusses (22 bar, 25 bar and 72 bar) with multiple loading conditions and design constraints have been considered. The results demonstrate that the Exchange Market Algorithm is very effective and efficient for the optimization designs of medium scale truss structural problems.

Portfolio selection is considered a critically significant decision, firms have to make. As such, much research has been focused on the selection of a portfolio with a controlled level of risk and high expected return. This paper uses a new definition of risk for portfolio selection whereby risk taking is taken as a curve instead of a specific value. In this paper, a genetic Algorithm is presented for portfolio selection. Stochastic simulation is used to calculate the expected values and the values of the risk curve function. Finally, as a case study, the Algorithm has been used for portfolio selection in Tehran Stock Exchange. The results of the Algorithm and the experiment show that the designed Algorithm is very effective for solving the portfolio selection problem.

IRAN and the world are moving away from central energy resource to distributed generation (DG) in order to lower carbon emissions. Renewable energy resources comprise a big percentage of DGs and their optimal integration to the grid is the main attempt of planning/developing projects with in electricity network. Feasibility and thorough conceptual design studies are required in the planning/development process as the most of the electricity networks are designed in the passed decades, not considering the challenges imposed by DGs. As an example, the issue of optimal placement and the capacity of DG’ s become problematic when large amount of dispersed generation is connected to a distribution network. Therefore, optimized Algorithms have been developed over the last decade in order to do the planning purpose optimally such as to alleviate the unwanted effects of DGs. In this article, after explaining the two proposed methods, the modified non-sorting genetic Algorithm (NSGA)’ s and Exchange Market Algorithm (EMA)’ s results, based on MATPOWER’ s systems have been compared, in order to find a fast and reliable solution to optimum planning.

Most of the Exchange rate determining models are based on the assumption of being determined in an efficient Market. Therefore, several methods for testing Market efficiency have been created and tested. Among them a modified go round random method was chosen. Having tested weak form of these methods in the Iranian Market during the period of 1370-78 based on weekly data, one finds that at the early stage of the period in question, the efficiency, even in the weak form was not approved. However, at the end of the period in question, since a stable foreign Exchange policy method was followed and as the Market expectation formation occured, some acceptable degree of weak efficieny was revealed by this test.

This study aimed to evaluate the significance and severity of the relationship between Market sentiment and the volatility of the Tehran Stock Exchange Price Index (TEPIX). We drew on the principal component analysis (PCA) to provide a composite sentiment index using a set of proxies. In addition, ARIMA-E-GARCH hybrid models were applied to model the volatility of the TEPIX and other control variables. Subsequently, GLS regression was used to measure the impact of Market sentiment and the control variables variation on the volatility of the TEPIX. The findings showed that the influences of optimistic and pessimistic sentiment on the volatility of TEPIX were both statistically significant and respectively, negative and positive. However, the severity of these negative and positive effects was slight. Furthermore, we found that the stock Exchange volatility was highly affected by the volatility of the inflation and the liquidity much more than the other variables such as optimistic and pessimistic sentiment.

The goal of present research is the analysis of different investment strategies, in two approaches of "Filter" and "Buyand Hold" in Tehran Stock Exchange Market. Since, the different investment strategies, according to above strategies, give different return rates, so, analysis of approaches lead to more return for investors is important, in accordance to, three hypothesis have been set, which will be shown in following:1- The average of monthly return of "Filter" approach is more than the average of monthly return of "Buyand Hold" approach.2- The importance of choosing "Filter" approach and "Buyand Hold" approach in different industries, is not the same.3- Decreasing or increasing the accepted Filter is reverse with its return.Present research includes; abstract, introduction, analysis of different investment strategies, methodology, analysis of data, and presenting results and applied recommendations.

This paper looked at the relationship between Stock Markets and Foreign Exchange rates, and determined whether movements in Exchange rates had an effect on stock Market in Iran. The Exponential Generalized Autoregressive Conditional Heteroskedascity (EGARCH) model was used in establishing the relationship between Exchange rate volatility and stock Market volatility. It was found that there was positive relationship between Exchange rate volatility and stock Market returns. Additionally, there is volatility persistence in most of the macroeconomic variables. It was also revealed that an increase (decrease) in trade deficit and expectation in future rise in trade deficit would decrease (increase) stock Market volatility. In addition, the consumer price index has a significant relationship with stock Market volatility.

Hedging is one of the most important topics in investment field, which could be noticed from different points of view. We evaluate the role of gold relative to different indices in Tehran Security Exchange (TSE) as a representative of Iran Capital Market. In this topic gold charecterristics of “ save haven” and “ hedge” versus TSE are studided. Daily Price Returns of 21 TSE stock indices and daily price returns of world gold (ons) are used as research data. Utilizing these data and GARCH model, two charecteristics of “ safe haven” and “ hedge” related to long position and short position of world gold for each stock indice is determined. This way it provide us with deciding on proper position in world gold, whether long or short position, to hedge downfall of a certain stock. In accordance with outcomes, we find long position in gold is not a strong hedge for non of the studied groups except for transportation indice. In addition, short position in gold is a weak hedge for two groups of non-metalic minerals and metals. Regarding safe haven, long position of gold played as a strong safe haven role for all groups in 10% quantile but not in non of 5% & 1% quantiles. Long position of gold is a safe haven for most of indices. However, there are little groups for which short position of gold is a safe haven.