نشریه مهندسی مالی و مدیریت اوراق بهادار
پیاپی 38 (بهار 1398)

Identification of financial market returns requires attention to the dynamics in the process of adjusting to the long-run equilibrium in these markets, and this is of particular importance to policy makers and investors of the capital market in view of the volatility of other markets, such as the foreign exchange market and gold in Iran. Has enjoyed. In this paper, the convergence between the returns of the stock market and the returns of the foreign exchange market, as well as the return on the stock market and the gold market in Iran, are based on daily data of gold prices, foreign currency and stock price index during the period of 10/10/2010 to 31 / The study of 1396/1496. The results of the coherent coherent patterns on the relations between these markets indicate that in the equation of stock returns and gold, a high diet that includes deviations from the equilibrium is greater than the threshold value, Iran is the dominant regime. Also, in the equation of returns of stock markets and currencies, deviations from long-run equilibrium below the threshold and in the low-level diet include more than 90% of the observations. But in the relationship between markets, the moderation rate in both regimes is statistically significant, and this adjustment is made for deviations greater than the threshold value more quickly.

The traditional data envelopment analysis model allows the decision maker unit (DMU) to use the most favorable weights to evaluate the efficiency. This type of evaluation with the most flexibility can prevent the full ranking of DMUs and the evaluation results for DMUs are unacceptable. To solve this problem in data envelopment analysis, a common weight approach based on the concept of the degree of satisfaction of a DMU has been introduced. Also, to solve a common weight model, which is a nonlinear model, an algorithm is presented that can be modeled step by step. In this paper, we will evaluate the performance of companies active in Tehran Stock Exchange using a common weight model for 24 companies active in Tehran Stock Exchange. The weighted average performance of Tehran Stock Exchange companies for the years 1394 and 1395. The results show that this method will rank companies without any interference during these two years.

The especial importance of capital market in countries is undeniable in economic development via effective capital conduct and optimum resources allocation. Investment in capital market requires decision making in new stock exchanges, and accessing information in the case of future status of capital market. Forecasting stock market price has always been a challenging task, since it is affected by many economic and non-economic factors and variables; therefore, selecting the best and the most efficient forecasting model is tough and essential. For this forecasting, we need a computing model with systematic method that can be estimated in this research. The attribution of this test considering one of the stock exchange industries is forecasting prices and contrasting them with calculated price achieved by Golden ratio algorithm. Banking industry is selected and all of listed in bourse and farabourse banks are reviewd that the results of one of them is  presented in this article.  Time-series and Fuzzy logic models are used for rationalization. Fuzzy time-series models have been utilized to make reasonably accurate prediction in the area of stock price movements.The mentioned  combined method are run on the average of weekly prices of Tehran Stock Exchange. In this research stock trade for investors with calculated relations are displayed.

The purpose of this paper is to present a new model of data envelopment analysis with network structure to evaluate the performance of Tehran cement companies. For this purpose, cement companies listed on the stock exchange during the years 93-95 were evaluated. The results showed that the new model can evaluate the performance of these factories - which have a network structure and include multiple indicators - and, in addition to commonly used financial and technical indicators, to consider undesirable outcomes and sustainability criteria in the supply network. Meanwhile, the mindset of decision makers about the preferential importance of some indicators relative to each other is also considered in the form of weight constraints to bring the efficiency closer to the real value. According to the results, the factories are divided into two categories: efficient and inefficient. Based on this new model, only 7 cement supply companies have been able to achieve efficiency within the three surveyed periods of the 42 listed companies.

Credit risk management in banks using a hybrid approachAmong the risks faced by banks, the risk to the bank is very high, and the lack of prevention and, in the event of a risk, lack of control and failure to investigate the causes and remedies, can lead to irreparable losses to the bank. It is a credit risk. To this end, raising awareness of the system in order to prevent and mitigate the risk and examine the issues and ultimately make a decision to address the problem has a special importance in the supervision of banks. The main objective of this research is to present a suitable model for managing credit risk in banks using the DEMATEL combined approach and network analysis process (ANP). In this study, 17 variables were identified using expert judgment (method Delphi) have been approved. The statistical population of the study is managers and specialists of the bank (Sardar Bank, Guilan Province). The tool used to collect the research data was a questionnaire. A total of 8 questionnaires were distributed among the research experts. Data analysis was done using the DEMATEL and ANP techniques. In this way, after the formation of a super matrix for comparing the criteria in ANP and solving the model, the coefficient of importance of each criterion was determined. The coefficients obtained in the next step were interfered.By analyzing data in the DEMATEL technique and process, it was found that among the 17 identified criteria affecting credit risk in banks, operational risk has the most impact on credit risk. A mong the operational risk criteria, the quality of the facility review process has the greatest impact. In other words, this criterion is the most important criterion in terms of impact and impact on the whole system. Also, the risk of focus is also of high importance throughout the system. The results of this research are useful in managing bank risk management.

Officials and executives from various businesses generally believe that the breadth of the stockholders' base has significant market interest. Although researchers have also agreed on the basis that shareholders are one of the key determinants of company decisions, few studies have been conducted on this variable. In this study, it was found that the increase of the stockholders base, unlike the developed countries, in Iran, is not in the interest of the companies. The results suggest that raising the shareholder base will increase the risk of conflict between investors and controlling shareholders. In addition, the findings show that this increase has a negative and significant relationship with the risk behavior and value of the company, and has positive and significant benefits with the dividend. In addition, the results of this study indicate that With increasing agency conflicts, the possibility of expropriating individuals outside of the organization will increase by the internal members of the company.

Stock liquidity risk can be considered as one of the most important factors in determining the expected returns of investors.Determining a suitable measure based on the characteristics of the company in the capital market that can help define the liquidity of the stock, would lead to a proper decision of investors. In this regard, in the present study, the effect of the systemic liquidity risk of assets (in particular stocks) in the Tehran Stock Exchange was investigated during the years 1385-1395.  In this research, the d non-trading days are used as liquidity indicators of stock trades.  It was found that, first, The co-movement between individual stock liquidity and market liquidity is not significantly related to stock returns. Second . The co-movement between market returns and individual stock liquidity is positively related to stock returns. Third, The co-movement between market liquidity and individual stock returns is negetivly related to stock returns.

The goal of any investor in the stock exchange is is to maximize returns with stock selection reasonably. In fact, the main concern of investors in the stock exchange is the stock selection or portfolio that are appropriate in profitability. The issue of stock selection involves creating a portfolio that maximize the utility of the investor. Therefore, in this study was investigated the use of F.MCDM combined to improve the performance of stock selection in the stock exchange in Cement Industry. The population of audit organization consisted of the experts of the study area and fully aware of the stocks who were selected through the convenience judgmental sampling in the two groups. In the first group, there were 20 top managers and senior experts of the organization who were chosen to localize the model and due to the specialized nature of the subject and the limitations to identify the experts, and in the second group, there were 6 experts as a statistical sample. It is a analytical and field study and an applied one regarding target. For this purpose, first the criteria identified by studying the scientific literature, and their validity was confirmed by university professors. The results are based on the fuzzy DEMATEL method indicated that "risk" is regarded as the most influential and "profitability" as the most impressible factor. Also, the results of the Fuzzy Network process analysis technique demonstrated that profitability is considered as the main criterion in improving the performance of stock selection in the stock exchange, especially in the cement industry, and factors such as market cluster, growth rate and risk factor are ranked respectively in the next. Eventually, based on the results obtained, some suggestions have been presented for managers and experts in the stock exchange.

An investor Constant relative risk aversion. pursues two goals of expected utility increases and reduces expected portfolio liquidity expectations. In the current study, the Constant relative risk aversion. utility using actual portfolio fluctuations, real asymmetry, real elongation of graphs and non-liquidity The portfolios were measured using the non-liquidity rate. Therefore, it is possible to directly select the options of the investor in the two-dimensional expected utility / liquidity space. This research was analyzed by using high frequency data on a set of 40 shares of Tehran Stock Exchange from 2011 to 2017 using MATLAB software and time retrieval methods were used for daily synchronization of transactions. Considering the expected returns of the portfolio and the expected liquidity over the minimum variance and the same weighted portfolio, the power coverage of this model is examined. The results show that in the different risk-incompatible levels, the expected liquidity of the expected portfolio is highly competitive and seems appropriate in terms of usefulness, liquidity, and expected utility, relative to the benchmark.

Prediction is an essential component of short and medium term planning in any business. A precise prediction can be effective in generating returns, managing cash flows, and allocating resources, enabling an investor to estimate, within a given time frame, its business revenue and its returns. Researchers have the idea to set aside old methods, which takes expense and time, and implement new methods such as the use of learning machines. This research is of the type of research, analytical-empirical, in terms of research design, post-event, in terms of purpose, applied, in terms of implementation logic, deductive and in terms of time, longitudinal and prospective type. In this research, the algorithm model of the nearest neighbor, the Rough method and the decision tree are used to improve predictive power, cost reduction, and time prediction of stock returns. For this purpose, a sample of 113 listed companies in the Tehran Stock Exchange during a 10-year period (2006-2015) was selected from the companies listed in the Tehran Stock Exchange. The results of the research showed that all the hypotheses of this research are based on a difference in the accuracy of estimating these models in the prediction of the three dependent variables.

In the current era, the study of the relationship between different markets and their impact on each other has become a necessity micro and macro investors. By investigating the relationship between markets, in addition to being able to obtain the required information about the impact of the markets, it can also help him in identifying various risks. According to the importance of the subject, in this paper, we have tried to investigate the relationship between the oil market and the gold, dollar markets, companies and energy funds in the field of energy, using the new associative rules approach and the Apriori algorithm. The use of associative rules explicitly explains the relationships between database fields and the relationships and interrelationships between a large set of data items. The results of this study indicate a direct relationship between the oil market and companies active in the energy sector, and the reverse relationship with the dollar index. There was also no significant relationship between the oil and gold market.

According to prospect theory, investors use reference points for their trading decisions; so that if stock price is below their reference points, they are unwilling to sell their stocks and therefore stock volume declines, but when the stock price exceeds their reference points, they are more likely to sell their stocks and accordingly stock volume increases. The identified reference points in previous researches are: purchase price, stock price in firm-specific events, IPO price and stock’s 52 weeks highs and lows.
In this research, stocks’s major historical highs and lows, without any time limits, are directly identified from price charts and are studied as reference points and to do so, the relation beween volume and these points is examined. The research Methodology is event study and by using panel data technique, the sample includes 52606 firm-week observations. Results of the research represents that when stock price reaches or exceeds major historical highs and lows, stock volume increases and therefore we can conclude that these levels are decision-making reference points for investors in Tehran stock exchange.

Asset and share liquidity regards two major subjects in financial literature. Liquidity increases firms’ attractiveness instock markets and reduces their risk and financing costs. According to the literature, one expect that firms with a higher value of intellectual capital intelligently pay more attention to their asset and shar liquidity. This research aims to investigate the impacts of intellectual capital on asset and share liquidity of companies listed in Tehran Stock Exchange. For this purpose, data for 147 manufacturing companies for the period of 1388-1394 was gathered. In order to measure intellectual capital Pulic model applied. To measure the asset liquidity the liquidity ratio, and to measure share liquidity, the liquidity rank of companies that announces by Tehran Stock Exchange was used. In orer to test the hypothese, multi- variable regression models with combined data method applied. The results indicate significant relations between intellectual capital with both asset and share liquidity in Tehran Stock Exchange, which means that companies with a higher intellectual capital are more liquid.

Today, in the famous financial markets, options and futures are very important contracts for reducing the risk of investors. Many active practitioners in the financial markets really believe that mispricing or incorrect valuation of these securities would be the main reason of collapse of some financial institutions. The complexity of option pricing/valuation, especially in the case of American basket options, as high dimensional options, has motivated many researchers to develop numerical and simulation-based models. In this paper, a new simulation-based approach for pricing/valuation of American basket option is proposed. Furthermore, for scenarios generation, we use a Monte Carlo simulation technique using a t-student copula-GARCH method and Extreme Value Theory to handle the nonlinearity of dependencies between variables. To verify the computational efficiency and the accuracy of the proposed methodology, we compare the results of prices obtained through the proposed models with those achieved through the Monte Carlo simulation and the method developed by Ju for European basket options.

Operational risk is not general definition and it has a unique definition for each company, which depends on the industry and the market of the company. The purpose of this research is to evaluate the effect of stochastic fluctuations on operational risk hedging European options on the S & P500 index. So this research will compare the operational risk level in the Markov Switching and Black Scholes models using the Var. The implicit volatility values for the three confidence levels of 90, 95 and 99% for different values of call options K, different maturity T, and different interest rate r were calculated for both models using S & P500 index call options information. The results of this study showed that due to higher gamma and random variation of operational risk, the coverage of transaction options in the Markov Switching Model compared to the Black Scholes Standard model was higher by using the criterion of value-at-risk op Var's coverage is at 90, 95, and 99 levels. The results show that OP VaR is inversely proportional to  ,    It also reduced doubling of the OP Variant's maturity over the agreed price. Finally, the results show that the interest rate has an asymmetric effect on OP VaR. As is clear from the figure, for K <S, the OP VaR has been lowered by rising interest rates, and for K> S interest rates have reduced OP VaR .

In this paper, I present an approach for valuing credit default swap (CDS), tranches of synthetic collateralized debt obligations and kth to default swaps. One-factor gaussian copula model is utilized to model default correlation for each pair of companies. In this research, I analyze the effect of different hazard rates and different default correlation between each pair of names on the spread to buy protection for multi-name credit products. The findings in the valuation of a tranche of a CDO show that if the correlation is low, the junior equity tranche is very risky and the senior tranches are very safe. As the default correlation increases, the junior tranches become less risky and the senior tranches become more risky. The valuation of kth to default swaps also shows that as the hazard rate increases, the spread of all swaps increases. Also, increasing the correlations between all firms while holding the hazard rate constant lowers the cost of protection in kth to default CDS if k is small and increases it if k is large.

The expansion of the capital market and the reduction of interest rates on commercial banks has made that investing in dominate shares as one of the most important opportunities for obtain gain on investment, which requires risk acceptance. In this paper, the goal is to extract the residual values of the logarithmic return of the Tehran stock exchange index using the CIPRA model. Then, using the extreme value theory, the extreme value model was obtained for these residual. Extreme value theory is a good approach to the estimation of high and low tails and measure such as Value Risk (VaR). In order to determine the performance of this method, another model was compared with this model using the two indexes include Tehran Stock Exchange and the Top 50 Industry Index at 99 and 99.5% for the estimated value of risk. The results of the backtesting show that the EVT-CIPRA approach works better.