درخت حوزه‌های تخصصی

Currently, in Iran's banking system, non-repayment of facilities has become one of the biggest issues, and due to the lack of a proper system for proper allocation of facilities, they face a number of problems, including the problem of allocation of loans, the problem of failure to repay loans Of the central bank, or the amount of facilities increased from the amount of reimbursement. The solution of this problem is the credit rating of the customers, which is based on a model based on the theory of fuzzy sets for validation of real customers of the Maskan bank of the East Azer-baijan in Iran in 2016. In this research a structured model was obtained for deter-mination and categorization of input variables for application in the system by factorial analysis then a expert fuzzy system was modelled that consist of six steps. In the first step a fuzzy system is designed that its inputs are financial capacity, support, reliability, repayment record and its outputs is customer credit. In the second step input and outputs are partitioned, in the third step thee partitioned inputs and outputs are converted into fuzzy numbers. The fuzzy inference is compiled in step four. In step five the defuzzifier is conducted. Finally the designed model is tested in step six. These results indicate research model efficiency compared to bank credit measuring experts that they predicate applicants performance according their judgment and intuition.

Information opacity leads to information asymmetry. In this situation, in providing their own financial needs, firms face limitations and inevitably provide their financial needs from the debt market by signalling private information to it. In addition, information opacity affects the leverage adjustment speed. This research investigates the effect of information opacity on deviation from target leverage and its’ adjustment speed during 2003 - 2017 in 131 firms listed in Tehran Stock Exchange. To estimate the research models, we use the regression analysis with panel data approach, the approach to control the effects of years and industries and the generalized method of moments with system estimator (system GMM). The research results show that the increase in information opacity increases (decreases) the positive (negative) deviation from target leverage. Also, research findings indicate that the increase in information opacity decreases the adjustment speed.

Study of volatility has been considered by the academics and decision makers dur-ing two last decades. First since the volatility has been a risk criterion it has been used by many decision makers and activists in capital market. Over the years it has been of more importance because of the effect of volatility on economy and capital markets stability for stocks, bonds, and foreign exchange markets. This research first deals with the evaluation of 8 various models to forecasting volatility of stock index using daily data of Tehran stock exchange. The used models include simple ones such as random walk as well as more complex models like Arch and Garch group. Forecasting volatility index method is developed in this paper. This method is based a random walk using a fuzzy logic approach. This method is used to fore-casting volatility of Iran stock exchange index. The proposed method is assessed by comparing other methods such as Moving Average, Random walk… Results show that our proposed method is compatible with existent methods.

Recent accounting and management literature shows that demographic character-istics of top management and corporate performance are related. Accordingly, using a two-stage least squares regression model (2SLS), this study examines the relationship between some management demographic characteristics including CEO tenure, gender and level of education with earnings quality and auditor choice. Sample includes the 420 firm-year observations from companies listed on the Tehran Stock Exchange during the years 2013 to 2017 and research hypothesis was tested using multivariate regression models. The results show a significant and positive association between managers education level and higher auditor quality choice. In addition, we find that firms with female directors in the composition of the board of directors and with higher education levels, have higher earnings quality. The current study is almost the first study which has been conducted in Iran, so the findings of the study not only extend the extant theoretical literature in developing countries including emerging capital market of Iran, but also help investors, capital market regulators and accounting standard setters to make in-formed decisions.

The present research proposes an automatic system based on moving average (MA) and fuzzy logic to recognize technical analysis patterns including head and shoulder patterns, triangle patterns and broadening patterns in the Tehran Stock Exchange. The automatic system was used on 38 indicators of Tehran Stock Exchange within the period 2014-2017 in order to evaluate the effectiveness of technical patterns. Having compared the conditional distribution of daily returns under the condition of the discovered patterns and the unconditional distribution of returns at various levels of confidence driven from fuzzy logic with the mean returns of all normalized market indicators, we observed that in the desired period, after recognizing the pattern, all patterns investigated at the confidence level 0.95 with a fuzzy point 0.5 contained useful information, practically leading to abnormal returns.