The Banking Crisis is previous decades caused the discussion of Systemic Risk in the financial market, including the Banks, has been taken into Consideration by Policy- makers. Based on this in this research using Delta Conditional Value at Risk ((COVAR)), the Systemic Risk in Iran Banking Section has been evaluated. For this reason, seventeen banks out of all ones which have been listed in Tehran Stock Exchange and the equity of their Owners from 1389 to 1395 was available, have been chosen. The results Show that (COVAR) for Khavarmianeh Bank Was the most (15.61) and for Sarmayeh Bank was the least (0.32). These results indicate that the crisis or disturbance in Khavarmianeh Bank more than the other Banks, affects the Financial System and Sarmayeh Bank has the least effect. In other words, any crisis in khavarmianeh Bank will give a rise of about 15.61 Percent to the Financial System Risk, while the corresponded Value for the Sarmayeh Bank is only 0.32 percent.

Abstract Value at Risk is the maximum expected loss of an asset portfolio under normal market conditions, over a given time horizon (one day, one month, or one week) and for a given confidence level. Determining Value at Risk is an attempt to provide financial managers with a certain number in which information about portfolio Risk is available in a condensed and summarized manner. Considering the shortcomings and weaknesses of Value at Risk, Artzner and his colleagues introduced the Conditional Value at Risk measure to cover the shortcomings of Value at Risk. In fact, the main purpose of the Value at Risk is to determine the maximum loss, but the Conditional Value at Risk determines the maximum loss in adverse conditions. These two criteria are defined in different ways. Failure to pay attention to it and wrong topic leads to misunderstanding and incorrect results.In this article, three different definitions of Value at Risk (and as a result, Value at Conditional Risk) are given, based on each of these definitions, the results, relationships and theorems will be different.

The use of variance as a Risk measure is limited by its non-coherentnature. On the other hand, standard deviation has been demonstrated as acoherent and effective measure of market volatility. This paper suggests theuse of standard deviation in portfolio optimization problems with cardinalityconstraints and short selling, specifically in the mean-Conditional Value-at Riskframework. It is shown that, subject to certain conditions, this approach leadsto lower standard deviation. Empirical results obtained from experiments onthe SP index data set from 2016-2021 using various numbers of stocks andconfidence levels indicate that the proposed model outperforms existing modelsin terms of Sharpe ratios.

Initially In this study, we introduce a new index called Revised Sharp (R-Sharp) for evaluation of portfolio in investment companies in Tehran Stock Exchange, and then examine this index were compared with the Sharp index. In the R-Sharp index, Value at Risk concept was used due to the properties of VaR and its application in the international financial institutions.The results indicate that the VaR calculation by GARCH is not applicable since time series data have not heteroscedasticity. Therefore, VaR was calculated for 10 investment companies by Risk Metrics method with  l=0.94 in coefficient level at 99.9%, 99% and 95% for 1-day and 10-day. In order to assess the accuracy of VaR calculation, the Wilcoxon signed ranks test was utilized. The results indicate that VaR Back testing at 95% and one-day period for all companies, were reliable.In this study, after calculating VaR and VaR Back testing, R-SHARP and SHARP indexes calculated for the period of study (2007-2010). The results show that there are some differences in the ranking of R-SHARP and SHARP indexes. So we tested the difference of R-SHARP and SHARP indexes by nonparametric tests such as Wilcoxon signed ranks test. Results of these tests indicate that sleight insignificant differences of indexes.

Initially In this study, we introduce a new index called Revised Sharp (R-Sharp) for evaluation of portfolio in investment companies in Tehran Stock Exchange, and then examine this index were compared with the Sharp index. In the R-Sharp index, Value at Risk concept was used due to the properties of VaR and its application in the international financial institutions.The results indicate that the VaR calculation by GARCH is not applicable since time series data have not heteroscedasticity. Therefore, VaR was calculated for 10 investment companies by Risk Metrics method with  l=0.94 in coefficient level at 99.9%, 99% and 95% for I-day and 10-day. In order to assess the accuracy of VaR calculation, the Wilcoxon signed ranks test was utilized. The results indicate that VaR Backtesting at 95% and one-day period for all companies, were reliable.In this study, after calculating VaR and VaR Backtesting, R-SHARP and SHARP indexes calculated for the period of study (2007-2010). The results show that there are some differences in the ranking of R-SHARP and SHARP indexes. So we tested the difference of R-SHARP and SHARP indexes by nonparametric tests such as Wilcoxon signed ranks test. Results of these tests indicate that sleight insignificant differences of indexes.

In this paper portfolio selection problem with interval optimization approach is surveyed. CVaR is Risk measure. CVaR is the expected loss depending on the chosen confidence level. Using CVaR makes the portfolio selection problem linear programming. Contribution of this paper is to consider mean expected interval; this development help portfolio selection problem to consider uncertainty. Interval optimization is modeling approach to consider parameters uncertainty in this paper. Considering uncertainty make model more realistic. The results of model show that this approach has computational efficiency and on the other hand proposed model produce better solution in Risk and portfolio rate of return point of view.

Portfolio selection,in order to maximize the profit from investment,is an important concern for minor and institutional investors.Therefore;efficient and secure optimization of financial assets is one of the most important new and modern,financial topics,trying to improve the portfolio performance using modern approaches of other sciences.Accordingly,this article aimed to optimize the index returns of top 10 companies of Tehran Stock Exchange from 2011 to 2015 using portfolio Risk minimization approach with the maximum yield according to Conditional Value at Risk and differential evolution algorithm(DE-CVaR) on a monthly basis.The results showed that differential evolution algorithm with the Conditional Value at Risk approach,had better Sharpe and returns ratios by CVaR Value compared to the random algorithm.The results of posttest with monthly approach also showed that DE-CVaR was better than random algorithm in terms of the criteria for selecting the optimal portfolio.