This essay is going to optimize the PORTFOLIO of stocks similar to the Markowitz approach. Nonetheless, the way in which the risk is measured is Foster-Hart risk. This measure was proposed by Foster and Hart in 2009. It takes into account the extreme events of losses. The theoretical definition could be as a minimum wealth that an investor should have in order not to face with bankruptcy. Our sample consists of adjusted daily data from thirty-four companies chosen from Tehran Stock Exchange’ s Top 50 Index in the period between 1391/07/01 and 1396/06/31. Data has been collected from Rahavard Novin software which is widely used in finance studies in Iran. Different OPTIMAL PORTFOLIOs has been achieved in this essay. Each of which uses a different method of risk like Cvar and Semi-Variance besides Foster-Hart. Results of this essay show that Foster-Hart OPTIMAL PORTFOLIO could have higher sharp ratio in comparison with the others.

In this paper, we developed robust optimization approach that departs from the randomness assumption used in other methods of optimization under uncertainty and describe uncertainty in parameters through uncertainty sets; for PORTFOLIO selection problem. The model can control the conservativeness of investor for PORTFOLIO selection by a defined parameter. We used 50 active company of Tehran exchange stock in 3 first months of 1392 to study the performance of model. The results of paired comparisons in out of sample experiments shows that Markowitz PORTFOLIO which has same expected return by robust PORTFOLIO, has lower Sharpe ratio.

Management of Foreign exchange reserves is important for every country. This matter is also of particular interest for Iran as an Oil exporting developing country. This paper designs an OPTIMAL PORTFOLIO for that part of foreign exchange incomes which is used for investment. Using the data on foreign exchange daily returns, for the period 2000-2008, and applying univariate and multivariate Garch models, we estimate a model which maximizes expected returns subject to a Value-at-Risk constraint. The results are examined using Backtesting, and then the most acceptable model is suggested. The results that the multivariate GARCH model is the most efficient method for selecting the foreign exchange OPTIMAL PORTFOLIO in Iran.

Price limits set up are adopted by many securities markets in countries such as the USA, Canada, Japan, and various other countries in Europe and Asia, to increase the stability of the financial market. These limits confine the price of the financial asset during any trading day to a range, usually determined based on the previous day's closing price. In this paper, we study the PORTFOLIO optimization problem while taking into account the price limit constraint. The dynamic programming technique is applied to derive the Hamilton– Jacobi– Bellman equation, and the method of Lagrange multiplier is used to tackle the constraint. Optimization problem solution results and numerical method show that the equilibrium path of wealth and investment in risky assets has a different pattern than the absence of price limits.

Choosing a stock PORTFOLIO is always one of the most important issues for investors. Theoretically, selecting a stock PORTFOLIO can be solved by minimizing risk assumptions with the help of mathematical relationships, but with the variety of choices in the capital market, mathematical relationships alone are not an effective solution. The variety of investment tools and the differences in the functionality of investors’ complexity have complicated the selection process. Now the expansion of financial and capital markets, the use of rule-based systems for quick decisions, with minimal risk and away from human error, design, development, or improvement of these systems can be a competitive advantage. In the present study, neural network algorithms and genetic programming algorithms have been used to identify effective features and the decision tree to improve id3 has been proposed as a method for predicting price and trend of stock price change to select the OPTIMAL basket. The research results show that in addition to reducing computational and memory overhead, the proposed method is able to accurately predict severe fluctuations with nonlinear patterns and compared to modern methods such as nearest neighbor search, linear regression, autoregressive integrated moving average, and time series prophet algorithm will do better.

One of the most applicable optimization approaches used in different sciences is Meta-heuristic Algorithms. This study, by new Meta-heuristic Algorithms, Symbiotic Organisms Search (SOS), introduces the model for selection of optimum PORTFOLIO and then the result is compared with the result of older algorithm, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). Therefore, the ten-month information of operation of 50 top companies in the Stock Exchange is extracted and estimated an optimized PORTFOLIO with the objectives of maximum efficiency and minimum risk by Symbiotic Organisms Search (SOS), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) is estimated. The results of the algorithm showed that despite the ability of these algorithms to PORTFOLIO optimization, SOS algorithm has a higher ability to optimization.

The development of analytical techniques in the investment PORTFOLIO in accordance with market conditions and economic climate can increase the dynamism of investment development and achieve greater returns against risk control. Forecasting and optimization techniques help financial decision makers to place the best stocks in their PORTFOLIO based on market information and achieve greater returns by optimizing it. The purpose of this research is predicting the effectiveness of the difference between Sortino and Markowitz PORTFOLIOs is based on the hybrid analysis systems algorithm. Accordingly, 102 companies of Tehran Stock Exchange were examined in the 2014-2018 period. In this study, by separating value stocks and growth stocks, random PORTFOLIOs were selected to test the research hypotheses and for analysis, two algorithms Support Vector Machines (SVM) and an Adaptive Neuro-Fuzzy Inference System (ANFIS) were used to select the most desirable PORTFOLIO. The results showed that Sotino (X) PORTFOLIO based on meta-heuristic algorithm (support vector machine algorithm) is significantly different from Markowitz (Y) PORTFOLIO, so that decision makers in Sortino PORTFOLIO seek to optimize their stock PORTFOLIO through long-term growth stocks. It was also found that the accuracy of the adaptive neural fuzzy inference analysis (ANFIS) system is higher than the accuracy of the support vector machine analysis (SVM) system to select the most effective PORTFOLIO from Sotino and Markowitz PORTFOLIO, because it has two learning mechanisms and Neural network optimization and linguistic expression of fuzzy inference help managers to make better estimates of uncertainty and uncertainty.

In the bank-based structure of the country's economy, banks are most responsible for financing, especially at the level of large projects. The purpose of repaying a loan through a syndicated mechanism is to reduce the undesirable risk and increase the effective loan rate. The statistical population of this study is the balance sheet information of the last five years (1396-1400) of banks listed on the Tehran Stock Exchange. In this research, the postmodern theory of PORTFOLIO based on variance of unfavorable data or half-variance-half-covariance has been used. To test the research hypothesis with the help of MATLAB software, the contact point of the efficient boundary of the model and the capital market line at different interest rates has been calculated and the OPTIMAL PORTFOLIO of syndicated loans has been determined. The results show,The payment of syndicated loans in the form of civil partnership and Mudaraba contracts has the highest interest and the lowest risk, and in contrast, forged loan agreements and installment sales have the lowest interest and the highest risk.

This research exploits Roy and Maiti model (1993) which is in respect of Fuzzy Goal Programming (FGP) in order to determine OPTIMAL PORTFOLIO and research goal is to determine (identify) OPTIMAL PORTFOLIO model using of Fuzzy Goal Programming and including it (its involvement) for two unique investment companies which are accepted in Tehran Stock Exchange. In data analysis, percentages scale less-making is used. Regarding to exerting the model in two unique investment companies during the years 1387 and 1388, research results represent that model application can provide a particular position for better and, more precision adjustment recognition- of investment companies PORTFOLIO in order for easier decision -making of investors.