فصلنامه دانش سرمایه گذاری
پیاپی 34 (تابستان 1399)

Today, economic crises and financial market uncertainties affect the stability of institutions and banks, which, as a result of instability from the financial sector, has led investors to achieve satisfactory returns with different constraints Has encountered an environment. The field of financial affairs in today's world is one of the major challenges facing third-world organizations and societies, and we are witnessing the emergence of crises that we are always seeing. Appropriate and timely decisions in this area are very effective in preventing economic, social, cultural and political harm, and plays an important role in creating peace and prosperity in the community. Making the right decision in the financial arena can be considered one of the most important skills of successful managers. In this paper, we try to introduce and explain a model for predicting banks' liquidity trap using financial statements data by collecting information and financial ratios of banks and credit institutions in Iran with the rial approach.

The development of financial markets requires the introduction of new models, forecasting and risk management. One of the indicators that are considered in risk management and measurement is value at risk index. In this research, the multivariate GARCH model has been evaluated to predict the value of exposed portfolio risk, including currency, stocks and gold, and the combined returns of gold price data, total stock exchange index and exchange rates from 2009 to 2016 were used. The results of VECH, BEKK, DCC, and VECH diagonal models have shown that the volatility of these variables in the estimation period is effective and this confirms the hypothesis of market independence in Iran, in order to evaluate the performance of these models in predicting VAR One-day prediction of conditional variance covariance matrix of models was used. The results of the post-test of the models using the coup and kristoferson tests showed the performance of all four models was appropriate and the comparison of the mean loss function of Lopez showed that the VECH model had better performance than other models. Despite the good performance of the VECH model, however, the estimation of this model is very time-consuming. due to the large number of parameters that are estimated in the estimation of VECH and BEKK models that lead to a reduction in the degree of freedom and, as a result, a reduction in the validity of the model, the use of these two models for portfolios with more than three assets is not recommended.

The purpose of the present research is to design a seamless optimized risk-based liquidity management model. The statistical population of this research is in the special holdings of social security investment company (SHASTA), Due to the limited statistical population, the total statistical society including the company holdings in the period 1391-1396 was considered as an example. The method of collecting information is library and field. Data analysis was performed using the multivariate regression model presented in the study using Eviews software. The results of the hypothesis test showed that there is a significant relationship between risk sensitivity, price fluctuations, expected returns fluctuations, liquidity risk, and liquidity risk with liquidity management.

The purpose of this study is to present an integrated management model for electronic supply chain of product and its effect on the National Iranian South Oil Company. Present study based on the purpose is an applied type and based on the nature is a descriptive - correlation type. The population under study consisted of all employees of National Iranian South Oil Company that 512 subjects were selected as sample. The data collection tool was a questionnaire that its reliability was confirmed using Cronbach's alpha, composite reliability and factors load. Validity of the questionnaire was confirmed using three methods of content validity, convergent validity and discriminant validity at partial least squares.Data analysis was performed using structural equations and partial least squares methods in SmartPlus software. The results showed that the proposed model is product fitted and the significant effect of integrated management for electronic supply chain and competitive advantage was confirmed on the performance of the National Iranian South Oil Company. But, the effect of the risk of electronic supply chain on the company's performance was rejected. Also, the results of moderator assumptions showed that competitive advantage affects the relationship between integrated management for the electronic supply chain and the performance of the National Iranian South Oil Company, but the risk of the electronic supply chain does not have a moderating role in this relationship.

Today, companies in the competitive market are required to produce products that respect environmental factors. And they must comply with the relevant standards (such as ISO14001). The purpose of this study was to identify and rank the green and green production factors through the AHP hierarchical process analysis method. The sampling method was purposeful and carried out in 2017. The research is a descriptive and applied research. With the comprehensive study of research background and deep interview with experts, seven major criteria of pure-green production have been identified and prioritized. Human capital management in the production process with the weight of 0.310 is the most important factor. The results also show that the three factors for developing employee participation and participation, the continuous improvement of the service delivery process, and the establishment of an environmental management system are the most important factors in reducing all aspects of assessment or types of waste in the pure green production system. These results in the form of non-monetary or sustainability reporting provide a comprehensive picture of the organization's activities and a balanced view of its effects and benefits in terms of economic, social and environmental dimensions, and as the financial measurement of the sustainability of companies is increasing , The risk assessment and expected returns of corporate governance performance will be possible with a sustainability approach, and investing in sustainability dimensions is considered to be a relative advantage for investors and is considered as one of the underlying factors of a trading position.

Abstract The main objective of this research is to estimate the demand model for crude oil and natural gas in the country during the period from 1988 to 2015 and also to predict crude oil and natural gas demand functions in Iran during the sixth development plan with the aim of studying the effect of important variables affecting their consumption in the country. VAR - VECM model is used to investigate the relationship and the effects of variables and the short-run and long-run relationship between variables, and finally, extracted model has been used to predict crude oil and natural gas demand in the country at 1400 horizon. The results indicate that: (1) income elasticity is low and the sensitivity of oil consumption to changes in income (here, per capita income) is small. (2) There are no long-term causal relationship between intrinsic independent variables and exogenous independent variables, such as oil price and natural gas prices, towards natural gas consumption and per capita income. (3) In the short term, there is no causal relationship from natural gas consumption, natural gas prices, oil prices, and per capita income towards crude oil consumption. (4) Variance decomposition for oil consumption variable indicates that in the long run, natural gas consumption has a significant contribution to explaining changes in crude oil consumption.

Ethical decisions among accounting professionals are still considered as an issue importand, because accounting fraud will never be stopped and will affect accounting. The literature on business ethics tends to refer to religious affiliation as an indicator of ethical behavior in financial decision-making approaches. The main purpose of this research is The impact of religious orientation on decision-making of financial managers. The present study was applied in a correlational approach and the required data were collected using a questionnaire and a financial scenario from a statistical society including 200 financial managers Companies accepted in Tehran Securities Exchange during the period of 2017and using the minimum structural equations Squares have been analyzed. The results show that the extrinsic religious orientation, has a significant and positive effect on pragmatic approach (selfishness). In addition, in financial directors with extrinsic religious orientation, the strongest approach is pragmatic decision making, and its weakest hermeneutical In addition, in financial directors with extrinsic religious orientation, the strongest approach is pragmatic decision making, and its weakest hermeneutical.

Identifying the behavior of prices in financial markets requires attention to the dynamics in the process of adjustment to long-term equilibrium in these markets and attention to this issue is necessary for policy makers of the capital market due to fluctuations of the foreign exchange market in Iran. In this paper, the asymmetric adjustment and dynamic behavior of foreign exchange and stock markets are studied. The results of Threshod vector autoregression and Threshold cointegration models on the relations between these markets indicate that the returns of stock and currency markets are cointegrated with a threshold adjustment, and the process of adjustment when stock and currency markets are adjusted to long-term equilibrium are asymmetric. Also, there is a much lower convergence of positive deviations (above the threshold) of long-term equilibrium with negative deviations (lower thresholds), and the deviation of the return on long-term equilibrium in the stock market in negative errors is adjusted to a higher rate than positive errors. And this adjustment is quite asymmetric and meaningful.

Nowadays, banks in the country are faced with serious problems in terms of their assets. One of the factors that led to this situation is the poor quality of banks' assets, which can be attributed to the lack of a rating system and an improper assessment of credit risk. This study predicts the probability of default during a specific time using the Cox regression model as well as the survival model of spline-based logistic regression. For modeling of credit risk, using these two methods, 10 variables related to 2861 customers of an Iranian bank were used. We compared two models using ROC method, the Cox regression model with AUC = 0.799 was more efficient than the spline-based logistic regression model with AUC = 0.746.

One of the most important topics in financial markets in recent decades is the forcasting. The main purpose of this study is to forcast volatility future prices. In this research, four groups of symmetric GARCH (GARCH), exponential GARCH, FIGARCH and multi-regime GARCH models have been estimated and forecasted using normal distribution, t-distribution and GED distribution. According to the model error for forecasting fluctuations, the Markov Switching GARCH model (MS-E-GARCH) is reported to be the most efficient model to forecast the fluctuations in the gold coin futures market. The results of the estimation by the Markov Switching GARCH model (MS-E-GARCH) show that fluctuations of gold coin futures market are predictable; and as a result the gold coin futures prices do not have the weak form of efficiency in both low and high volatility settings and systematic profits could be achieved in this market. According to the results of the study, the accuracy of MS-E-GARCH model is higher for GED distribution in comparison with other models.

This study aims to present an intelligent model for predicting financial opulence in the security companies as a system that supports the decisions. For this reason, by investigating background of the seventeen numbers of variables as a predictor variable for predicting the class of financial opulence from valid sources of central security Site G.A.A during the years 1390- 1395 had been extracted. For conducting this investigation, there had been used of the data of Security Industry, during the years 1390 to 1395. In this investigation, first, we compare the results of applying different models of prediction based on Data Mining and in the second stage, we investigate the ranking of predicting algorithms. The finding results of this investigation showed that the financial opulence with acceptable precision is predictable and the extracted model by using the decision tree has very high precision and capability.

This study presents the new hybrid network of GARCH family and an artificial neural network to predict the Tehran Stock Exchange index during the period of 2008-2017. The existence of long-term memory in the conditional variance of the Tehran stock returns causes use in addition GARCH and EGARCH models with short- memory, long-term memory models. In addition to long-term memory models, considering the better performance of hybrid models in predicting financial data of the Garch family models (short and long-term) are combined with the artificial neural network. Using hybrid models the return of stock index was forecast for the next 10 days and its accuracy was evaluated using the evaluation criteria. The results showed that the hybrid FIEGARCH with the student-t distribution model was more efficient in forecasting return of stock and had a lower forecast error than others models

The problem of portfolio optimization and stock selection is one of the major areas for financial investors in financial markets. In this paper, some of the challenges of simultaneously multi-objective portfolio optimization are addressed. Four different models are designed: a fuzzy multi-objective programming model has been used to consider the multi-criteria nature of stock selection and the uncertainty associated with the return on assets and a simple model for doing this. The models are designed in such a way that both the nature of the multiplicity of the problem of portfolio selection is considered and the considerations of the investor in the choice of portfolios are involved. After designing the evolutionary 3 and 4 objective models of portfolio optimization, multi-objective evolutionary algorithm NSGA-II was used to solve this models. Concretely, it optimizes return, the downside-risk, skewness and the Kurtosis of a given daily returns, taking into account budget, and investor constraints. Because of the NP-HARD nature of the above models, the NSGA-II proprietary algorithm was coded in the MATLAB, and after solving each model and extracting the Pareto frontier, the best portfolio on the Pareto front was selected based on the maximum Sortino ratio. Finally, the results of the obtained portfolios in both fuzzy and non-phase conditions were compared according to the trainer's ratio, and it was determined that the use of fuzzy logic in quadratic evolutionary algorithms, compared to a situation where fuzzy logic is not used in the design and use of these algorithms., Creates more favorable results.

The purpose of this paper is to investigate the susceptibility of turbulence in returns between different industries of Iran's capital market for active industries in the Tehran Stock Exchange during the period of 1384-1394. For this purpose, panel data and CCX criteria for risk avatars were used. The results of this study indicate that for the full period of the research sample and for considering the period of recession and crisis in the stock market, the results indicate the effects of overflow in the active industries in the stock market. Estimated coefficients for tipping effects in the sample indicate that in most of the companies surveyed, the effect of overturning is significant. Also, the estimated coefficients for considering the period of the crisis in the stock market indicate that the coefficients are positive for the effect of the outflow in the stock market. Also, in the case study, there is a probability of financial risk fluctuation between the investigated industries. Based on the results, it can be stated that the CCX value and the significant level reported in each section have a negative relation with the amount of direct and value related debt and investment activities. Therefore, the economic sectors that have high debt financing, low value and investment, are in the midst of financial crisis, the initial candidates for fluctuations and declining stock prices. Evidence suggests that those industries that are more competitive will expose the risk sequence more strongly.

The main aim of this paper is to examine the role of financial and non-financial criteria of balanced scorecard in portfolio selection using modern technique of Potentially Pairwise Rankings of all possible Alternatives (PAPRIKA), from the view point of professional and non-professional investors. To this purpose and through theoretical literature, and by adaption of factor analysis method effective factors were identified and chosen in stock selection. Then with respect to responding of professional and non-professional investors to the questions, and using of PAPRIKA multivariate decision making model by them, these criteria were ranked. Initially, 60 variables were used in this study and then after conducting exploratory factor analysis they were reduced to 29 factors. The results of this study indicate that the first six variables effective on stock selection for professional investors respectively include variables of profitability growth, solvency, return, return on assets and equity, customer’s satisfaction, price-to-earnings ratio; and for the non-professional investors, they comprise of price-to-earnings ratio, return, profitability growth, solvency, return on assets and equity, di-rectors' ability. Similarly, the results of the study show that compared to non-professional investors, professional investors attach more importance for non-financial criteria of balanced scorecard.

This paper analyses the effects of investor sentiment and Free Float on stock price, based on Stock return. This study Uses data from firms listed in Tehran Stock Exchange over a period of 6 Years (2010-2016)and constructs investors' Sentiment Index and examines investors' sentiment effect on Stock return. Based on current expectations, when the free float is more, more deals done and consequently the share price volatility will also increase. Shareholders expect more profits from stocks which have more free floats. In this study, in order to increase the degree of confidence in the results, has been used Dynamic Panel method and estimation of the equation generalized moments (GMM).The findings of this study indicate that there is a positive and significant relationship between investor sentiment and free float stocks and stock returns.

The need to achieve optimal portfolio optimization criteria, which, in addition to the accuracy of investment decisions quickly, goes beyond academic needs, as investors, investment companies and investment managers need to reduce their investment losses, increase Risk-adjusted returns have always been discussed. However, it is very difficult to achieve a portfolio optimization method that fills the gap between applied requirements and theoretical models. Considering that one of the most important factors in achieving optimal returns is diversification. This research, with the theme of "Formation of optimal investment portfolio in Tehran Stock Exchange using hierarchical and K-means clustering methods", attempts to present a suitable method for portfolio optimization using market data and clustering. The result of this comparison will clarify the success rate of cluster optimization compared to the index portfolio.

The present study is attempts investigate the impact of financial statement comparability on corporate financial cash holdings. To this end, three various proxies based on DeFranco et al’s (2011) were employed to evaluate financial statement comparability, and Ozcan & Ozcan’s (2004) model was also used to measure cash holdings. The research hypothesis was also developed based on the data collected form a sample of 82 firms listed on the Tehran Stock Exchange during the years 2013-2017, and then tested using multivariate regression model based on panel data. The results indicate that financial statement comparability reduces the level of corporate cash holdings. This finding means that, financial statement comparability can mitigate uncertainty and facilitate the monitoring of the evaluation of the managerial performance through attenuating acquisition costs and enhancing the quality and quantity of the information available to investors. Accordingly, firms with comparable financial statements confront with less external financing costs and restrictions, thereby less likely to hold cash. Moreover, these results are robust and are not sensitive with respect to alternative measure of cash holdings and individual analysis of the research hypothesis for each year.

Abstract The Tehran Stock Exchange has always seen a lot of fluctuations. Price volatility is a part of the market's nature, and one of the main issues in the capital market is to explain these fluctuations using fundamental patterns. However, sometimes these fluctuations go out of their normal form and place themselves in bumpy bumps and sudden crash (crisis) and bring irreparable blows to the stock market. Therefore, in view of the importance of price bubbles, this study presents a model for estimating the likelihood of price bubble formation in the capital market and the main objective of the Tehran Stock Exchange. The statistical sample of this study is the 166 companies listed in the Tehran Stock Exchange between 2007 and 2017. In this study, using spss software and runs test, Skewness and Kurtosis test. we investigated the probability of price bubbles, and then, in order to provide a model for price bubble, the factors influencing price bubbles based on the proposed model have been investigated. The results indicate the probability of bubble occurrence in companies admitted to the Tehran Stock Exchange. Also, results shows that shareholders, P / E ratio and liquidity rate have a significant effect on price bubbles. However the size and transparency of the information did not show a significant effect on the price bubble.

The purpose of this research is to analyze the paradigmatic content of financial performance deficiencies of Abadan Oil Refining Company in 2019. For this purpose, the study was conducted in both qualitative and quantitative form. In the qualitative part, the factors and indicators affecting the financial performance deficiencies of the firm were estimated by the Grounded Theory method and in the quantitative part, the structural equation model was estimated. The results show that causal, consequences and intervening factors had the highest impact among the factors affecting the financial performance of the firm. Among the context factors, respectively, the existence of a monopoly market and government pricing, the lack of international communications, and the lack of revision of the bylaws have the most impact on the financial performance failure. Among the causal factors, copying plans and ideas, the lack of dynamic internal control mechanisms to produce clear financial data and the lack of transparent reporting in the financial statements have the greatest impact on financial performance failure. . Among the intervening factors, high inflation, severe exchange rate fluctuations, and the inability to supply equipment and components needed from overseas have the greatest impact on financial performance failure. Of the strategies, only lack of international communication has been significant; and of the consequences, the loss of credibility, the inability to compete in the industry, and the diminishing of customers have the greatest impact on the firm's financial performance failure.

The aim of this study Modeling and Identifying Hierarchy of the Effective Measures of Negative Criteria Skewness on Stock Returns and the Extra Sigma of Stock Price Crash Risk in the Tehran Stock Exchange with Panel Data Approach. For this purpose, the financial statements of 119 companies were collected during the period 1390-1396. Multivariate regression with panel data was used to test the hypotheses. The findings of the study indicate that debt maturity, conservatism, political connection, financial constraint, stock liquidity, business strategy and institutional ownership are the most important factors influencing stock prices crash risk. The findings of the study indicate that debt maturity, conservatism, political connection, financial constraint, stock liquidity, business strategy and institutional ownership are the most important factors influencing stock prices crash risk.

A capital market is a sample of human society in which there are networks of traders. Because of traders, a sociological approach to capital market indicates that traders and capital market influence each other. Therefore, in our research we hope to discover a suitable index to analyze the capital market based on sociological approach. This research is a descriptive – survey model. The Statistical society is very large and complex. Therefore we have chosen 150 people who are working in the capital market as sample of our society and we have sent questionnaires for them. The result of the data ran in SPSS software in two different ways. The first way was through descriptive statistics and the second way was inferential statistics. Then, we used SMART PLS software for modeling the structural equation. Experimental results show that financial knowledge, risk perception, feelings about market indexes, value of money and objectivity are the suitable indexes for the analysis of the capital market based on sociological approach.