درخت حوزه‌های تخصصی

Investigating the performance of companies is one of the most important issues for the users of accounting information. The purpose of this study was to provide evidence about the effect of asymmetric appropriateness on investors' expectations. The results of the research on accepted companies In the Tehran Stock Exchange during the period from 2012 to 2016. To collect data, a library method was used and referring to financial statements, explanatory notes and monthly stock exchange of the Stock Exchange. Using Cochran sampling method, 120 firms were selected as the statistical sample. To analyze the data, multivariate regression analysis was used to confirm the rejection and research hypotheses (ivyz software). The results showed that asymmetric accountability leads to different expectations of investors about the company's outlook, and the negative relationship between asymmetric verification (conservatism) and investors' controversy is weaker with the release of good news and gets worse by the publication of bad news. The results are consistent with the documentation referred to in the theoretical framework of financial research and literature, such as the theory of vision and the concepts of behavioral and financial behavior, and the publication of good and bad news has a significant role.

The current research sets out to identify and scrutinize the impact of the CEO’s perceptual biases in judgment and economic decision-making on the reporting quality of the firms listed on the Tehran Stock Exchange. Adopting a mixed method, the present study first seeks to detect the components and indices of CEO’s perceptual biases via critical appraisal and with the special participation of 10 accounting experts. Afterwards, the rec-ognized indices are set to undergo a Delphi analysis given the mean and the coefficient of agreement. The verified indices are then adapted to the ac-counting models and analyzed in the form of research hypotheses. The re-sults of qualitative analysis using Delphi method verify the reliability of 16 indices out of 22 ones. Regarding the quantitative analysis, the association between the indices of the CEO’s perceptual biases in judgment and econom-ic decision-making, and the primary proxies of financial reporting, namely reliability and competitiveness is tested. The findings reveal that the indices of the CEO’s perceptual biases in judgment and economic decision-making exert a significantly negative effect on financial reporting reliability and competitiveness.

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.

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.