فهرست مطالب esfandyar malekian

The aim of this research is to provide an optimal model for professional auditing oversight in the Iranian Association of Certified Public Accountants. To achieve this research goal, research data were collected by consulting experts in the field of auditing. The research population consists of knowledgeable experts in the field of auditing, and in line with the research objective, they were selected for interviews using a snowball or chain sampling method. In addition to the conducted interviews, in order to enhance the credibility and comprehensiveness of the research, documents and materials related to professional auditing oversight were carefully studied, examined, and analyzed. The results of the research indicate that monitoring compliance with laws has been identified as the primary and initial causal factor in controlling the quality of auditing institutions.In addition to the conducted interviews, in order to enhance the credibility and comprehensiveness of the research, documents and materials related to professional auditing oversight were carefully studied, examined, and analyzed. The results of the research indicate that monitoring compliance with laws has been identified as the primary and initial causal factor in controlling the quality of auditing institutions.

Due to limited cognitive resources, investors often utilize mental shortcuts to make quick judgments. This study examines the impact of representativeness heuristics (Conjunction Fallacy, Gambler's Fallacy, and Stereotypes) and the Cognitive Reflection Test (CRT) on investor decision-making. The population of this study consists of a sample of investors in the Tehran Stock Exchange. The study employs a Chi-Square test (χ^2) to explore the relationship between heuristics and CRT, along with T-tests, one-way ANOVA, and correlation analyses to identify individual differences. Results indicate that proper utilization of cognitive resources can partially prevent the Conjunction Fallacy from occurring. Moreover, investors tend to consider the high probability of consecutive results for an event regardless of cognitive resource usage. Interestingly, this study also found that investors with lower CRT scores made decisions less influenced by stereotypes. We conclude that reducing the impact of representativeness heuristics can be achieved through knowledge and experience gained from similar situations and appropriately utilizing cognitive resources.

The aim of study is presenting a model of excellence with the paradigmatic approach of "marketing based on the code of professional conduct" in audit institutions. The current research is conducted using a grounded theory in 2022. The research community consists of partners, managing directors of audit institutions, and people with an experience of membership in the Board of Directors of the Society of Iranian Certified Accountants that 26 of them were selected as a sample by purposive sampling. The data collection tool was semi-structured in-depth interviews. The findings showed more than 165 unique initial coding, 62 intermediate coding and 25 advanced coding. Among the most essential elements of the presented model are causal conditions (such as financial problems of institutions), intervening conditions (such as buying comments), contextual conditions (such as structural features of the profession), consequences (such as realization expectations of key stakeholders) and strategies in two levels of implementation (such as management of relations with owners) and control and correction (such as market audit). The present study can be considered as the first attempt in the field of providing a model of excellence specifically in audit institutions with an emphasis on the code of professional conduct, which leads to the introduction and application of marketing concepts and the improvement of marketing knowledge in audit institutions.

The research objective is to develop a model for evaluating information quality of reporting entities using network data envelopment analysis (NDEA) models. The main motivation is the multidimensional feature of information quality concept with respect to the proxies and consequences of information quality along with the capabilities of DEA models in evaluating efficiency of decision-making units (DMUs: here the reporting entities) based on different inputs and outputs. In this regard, firstly the most important proxies and consequences of information quality are extracted from literature review and secondly considered as inputs and outputs of consequential two-stage NDEA model depending on their relationships with information quality concept and finally the information efficiency of reporting entities measured using simultaneously the proxies and consequences of information quality. The results revealed differences in DMUs' information efficiencies in different stages suggesting classic viewpoint deficiency of DEA models in evaluating DMUs' efficiency. Moreover, DMUs' efficiencies in first stage (proxies of information quality) are greater than their corresponding efficiencies in second stage (transforming proxies to consequences) and network efficiencies, resulted from optimization of all distinct stages, take an amount between first- and second-stage efficiencies. Among other results of the research in addition to providing a unique amount of network efficiency, is giving explanations for network and its components inefficiency, and identifying benchmarks for optimizations of inputs and outputs of each stage and overall network and setting a way to efficient frontier.

Accounting rules mandate that the cost of debt should be recorded as an expense, while the cost of equity does not appear in the income statement. Therefore, the amount of financing expense, and thus net income, in the income statements depends on how firms finance their business. In this study, the effect of changes in financial leverage and interest expense have been studied on revenue-expense matching in the companies listed on the Tehran Stock Exchange. The sample includes 199 companies listed in the Tehran Stock Exchange from 1383 to 1397. The results show that revenue-expense matching is higher for companies with a large reduction in financial leverage. In addition, incremental changes in the financial leverage have a negative effect on the simultaneous relation between revenues and non-operating expenses matching.  Also, the results show that only reduction changes in interest expense led to an improvement in simultaneous revenues and non-operating expenses matching. In general, results indicate that differential accounting treatment of the costs of debt and equity can affect earnings attributes through a change in capital structure

This study aimed to investigate the relationship between voluntary disclosure and earnings management and financial performance during the life cycle of the listed companies in Tehran Stock Exchange. The statistical population of the study included all listed companies in Tehran Stock Exchange since 2013-2018. In this study, earnings management, the financial performance of the companies (including return on equity, returns on assets, Tobin Q ratio, economic value-added, and refined economic value added) were the dependent variables, and the level of voluntary disclosure was the independent variable and the life cycle of the company was considered as the moderating variable. Also, in order to test the research hypotheses, a linear multivariate regression model using combined data was used. The results showed that earnings management and financial performance indicators have a significant relationship with voluntary disclosure over the life cycle. Accordingly, an increase in the level of voluntary disclosure increased the company's performance. Also, the results of the study indicated that the company's life cycle mediates the relationship between the level of voluntary disclosure and the company's performance.

This study investigates the effects of board of directors' characteristics on environmental, social and corporate governance, ESG, reporting in the companies listed in the Tehran Stock Exchange during 2012-2016. Data was collected using document mining method and referring to databases. This is inferential with correlation-based statistical analysis research, based on structural equation model. The results showed that among the eight variables explaining board of directors' characteristics, the ratios of non-executive members of the board, corporate ownership in the board, board of directors stability and number of women in the board have positive and significant impacts on ESG reporting; and CEO duality and level of education of the board have negative and significant impacts on ESG reporting. But the variables of the size of the board and the number of meetings of the board are uncorrelated with the ESG reporting. The results of the research hypotheses show many of the board of directors' characteristics have important role in the ESG reporting. This indicates the factors needed to be considered to improve the transparency of information.

This study investigate the relationship between Bid-ask spread and depth of market in Tehran Stock exchange. The main objective is to answer that “wheter there is the relationship between bid-ask spread and the debth in market”. The statistic community are companies in TSE. We select48 companies from these statistic communities during 1387-91 by restricting the companies that meet some criteria for doing the research.we have used two categories of information for studyng the above mentioned objective.The first is library and the second is secondary data.We used two variable as control varibles; size and valume. For assessing research hypothesize the software “SPSS”; liner regression were used. the findings show not significant relationship between undependent variable and control variables with dependent variable.

One of the most important methods of opacity accounting information by management is to accelerate the identification of good news versus delaying the identification of bad news on profits, but there is always a final level of accumulation of bad news in the company, and by reaching that its final level, these bad news will be released, which will lead to a Stock Price Crash Risk. In fact, stock price collapse is a phenomenon in which stock prices are subject to severe negative and sudden adjustments. Accordingly, the first purpose of this research is to model the Stock Price Crash Risk of the listed companies at the Tehran Stock Exchange by using an optimal algorithm The cumulative particles and comparison with the results of logistic regression model. To this, a hypothesis was developed for the study of this issue and the data of 101 listed companies of Tehran Stock Exchange for the period between 2010 and 2014 were analyzed. First, 14 independent variables were introduced as inputs of the combined genetic algorithm and artificial neural network, which was considered as a feature selection method, and 7 optimal variables were selected. Then, using particle cumulative algorithm and logistic regression, predicted The Crashs. To calculate the Stock Price Crash Risk, a Stock Price Crash Period criterion has been used. In The Second Stage, the particle algorithm was used as a feature selection, and this time, to calculate the Crash risk, the NCSKEW criterion was used. Finally, the optimal variables were entered into the Ant Colony algorithm and the results were compared with the multivariable regression. In the second step, MSE and MAE were used to compare the results. The results of the research show that the particle Swarm Optimization and Ant colony are more able than traditional regression (lojestic and multivariable) to predict the Crashs. Therefore, the research hypothesises are confirmed.

In order to set precise, as well as fair standards and regulations, it is necessary to recognize agency relationships, and insurance industry stakeholders’ rights, in conjunction with their interests. In this respect, authorities in charge of the compilation of international and national accounting standards are trying to provide appropriate standards, combined with their requirements for financial reports by precisely recognizing and sketching the relationships among insurance industry stakeholders. Iran's Standard Committee has introduced "Accounting Standard No. 28" in the year 2006 for general insurance activities. The present paper studies the adequacy of accounting standard requirements by assessing the influence of the calculation methods of financial factors on two indicators of "benefit" and "solvency" which stand for the stakeholders’ interests and profits, respectively. According to the results, "Accounting Standard No. 28" is not adequate enough to unite the rights of the stakeholders (insurer & insured), as far as general insurance activities are concerned.

The stock price crash risk is an indicator for measuring risk asymmetry and is of great importance in analyzing portfolios and pricing asset holdings. Considering the importance of the risk of collapse, several studies have examined the effective factors on it, all of which use traditional methods of forecasting, while in recent years, new methods of hypermetricity have been widely used in other financial issues. It has been used and has had better results. The purpose of this research is to model the stock price crash risk of listed companies in Tehran Stock Exchange using the genetic algorithm and compare the results with logistic regression. For this purpose, a hypothesis was developed for the study of this issue and the data of 107 Tehran Stock Exchange listed companies for the period of 2010-2010 were analyzed. First, 14 independent variables were introduced as inputs of the combined genetic algorithm and artificial neural network, which was considered as a feature selection method, and 7 optimal variables were selected. Then, using genetic algorithm and logistic regression, predicted risk Stock price collapse. The risk of falling stock prices has been used to measure the risk period. The results of this study indicate that a genetic algorithm based model is more capable of predicting the stock price crash risk than logistic regression. Therefore, the research hypothesis is confirmed.