فصلنامه مطالعات تجربی حسابداری مالی
پیاپی 71 (پاییز 1400)

Because of the benefits of political connections and lower necessity of responding to market pressures to increase information quality by politically connected firms, it is expected that these firms will provide low-quality accounting information. With respect to the extended role of government in Iranian economy, this study aims to investigate the relationship between political connections and accounting information quality in the listed firms in the Tehran Exchange Stock (TSE). The statistical sample includes 101 listed firms in the TSE between the years 2010 to 2018. Financial restatement and intensity of financial restatement are used as the criterions of low quality of accounting information. To achieve the research objectives, two hypotheses have been proposed and to test the hypotheses logistic regression and multiple linear regression analysis in a panel data mode were conducted. The results show a positive relationship between political connections and occurrence and intensity of financial restatement. Therefore, it seems that the firms' accounting information quality is impacted by their political connections.

The herd behavior of investors is of the most noticeable issues in finance. Herd behavior could lead to increase in volatility of share prices and its deviation from intrinsic value. There have been some investigation on this issue in recent years which prove the presence of herd behavior in Tehran Stock Exchange. However, few of them seek to study the impact of various stock traits on investors’ behavior. This study aims to regard the idiosyncratic risk as a possible determinant of herding and consider its influence on extreme market condition, up and down markets. Using companies listed in Tehran Stock Exchange between 1388 to 1394, the results demonstrate that the idiosyncratic risk could intensify the herd behavior of investors in extreme down markets. In addition, in stock with lower idiosyncratic risk, herding can be observed in down markets.Keywords: Idiosyncratic risk, Herd behavior, Extreme market condition, Up and down markets.

The purpose of this study is to investigate the relationship between financial report readability and stock return synchronicity with the moderating role of institutional ownership and information asymmetry in companies listed in the Tehran Stock Exchange (TSE). This research is in terms of its purpose and its period is from 2015 to 2019 and the selected sample consists of 171 companies listed in TSE. To test the research hypotheses through panel data, the ordinary least squares regression method in Eviews software was used. The findings of the research hypothesis test show that there is a negative and significant relationship between financial report readability and the stock return synchronicity. Also, institutional ownership as a moderating variable negatively correlates the illusion of financial report readability and the synchronization of stock prices. Additionally, the moderating effect of the information asymmetric variables on the relationship between the financial report readability and the price synchronization is positive and significant. According to the findings of the research, it is necessary to examine, on the one hand, how readable the financial report readability is affected. On the other hand, in order to improve the market, more attention was paid to the issues affecting the stock return synchronicity.

Sometimes companies file fraudulent financial statements for tax fraud. The purpose of this research is to combine data mining tools and artificial intelligence with meta-heuristic algorithms to explain and optimize a model for detecting fraud and tax evasion by using the financial reporting capacity of companies. In order to collect research data, the financial reports of companies listed on the Tehran Stock Exchange, including 1056 years-company in the years 2007 to 2020 were examined. First, the effect of qualitative and quantitative indicators derived from financial reports was investigated, refined and then used to form the explaining model in the Adaptive Neural-Fuzzy Inference System (ANFIS). The model was combined and developed in the optimization stage with the aim of maximizing detection power, by using meta-heuristic optimization algorithms including genetic algorithm, particle swarm optimization algorithm and differential evolution algorithm. The research findings show that in terms of predictive power among the optimization algorithms used in the research, the particle swarm algorithm with the highest percentage of correct prediction, produces the most optimal model and in examination by test and training data is the most efficient algorithm. The results of the research indicate that the use of different optimization algorithms in the data mining approach increases the predictive power of the fraudulent fiscal reporting model.

Today, whit rapid and continuous changes in the business markets, many manufacturing companies compete to produce quality products, meet the uncertain demands of customers and reduce costs. Therefore, in today ˈs competitive market, a growing number of companies to implement profitability and to increase the importance of long-term sustainability and ling-term financial stability, diversification by changing their business to new product segments or global markets to achieve sustainable customer satisfaction, Gain a competitive advantage over competing companies. On the other hand, increasing the variety of products, inventory management, timely action and valuation methods used inventory, is one of the important issues in different companies. Because excess amounts of inventories can impose significant costs on the company. For this reason, companies are trying to minimize the associated price items by managing inventories. Accordingly, inventory management is one of the most widely studied operations management topics. Therefore, applying product diversification strategy and international diversification affects the performance of companies ˈs inventory. To conduct this experiment, the data of 120 companies listed on the Tehran Stock Exchange since 2009-2018 have been analyzed. The results show that related and international diversification has a positive and significant effect on inventory performance. Findings also indicate that unrelated diversification has an adverse effect on inventory performance, but this relationship is not statistically significant.

In this study, we examine market reaction to the asset revaluation of companies listed on the Tehran Stock Exchange. To do so, we first estimate the market reaction to asset revaluation announcement. We then explore potential explanations for the market reaction to the revaluation. Asset revaluation can improve firm's access to financing by improving financial ratios; On the other hand, the increase in firm's capital from the revaluation is accompanied by stock split and, as a result, a decrease in the theoretical share price. This apparent drop in theoretical share prices could induce shareholders' interest as a result of money illusion. To investigate these alternative explanations, we run a cross-sectional regression of the cumulative abnormal return on proxies of each factor. To further explore the driver of market reaction, we examine whether firms that have re-evaluated their assets experience improvement in their access to finance or a reduction in their financing costs. For this purpose, we study a panel of listed companies between and for their access to finance, financing cost, investment, and financial leverage, controlling for firm and year fixed effects. Our results are more consistent with the theoretical price reductions causing the market reaction. We do not find evidence of asset revaluations leading to the firm's better access to financing.

The risk of stock price Crash is one of the topics of interest in capital market research. Since the main mission of capital market regulators is to protect the rights of investors, it has always been important to consider the factors that affect Crash risk. The quality of financial reporting and earnings management patterns are the most important tools available to regulators that can help them manage crash risk aversion, which is why this study addressed them. Earning management patterns include earning management through Accruals and Real. The statistical population of this study is the companies listed on the Tehran Stock Exchange and the research sample was selected in terms of some features (including 167 companies) in the period 2012 to 2018. The research method of the present study is descriptive-correlation and the research hypotheses were tested using the generalized least squares method. The results showed that the accrued earnings management model is related to stock crash risk and the use of earnings management through accruals increases the risk of stock price falls. While this is not the case with earnings management through real activities, the application of this earnings management model has nothing to do with the negative changes in stock returns. In addition, audit quality reduces the relationship between accrued earnings management pattern and stock crash risk. While the relationship between real earnings management pattern and stock crash risk is not affected by audit quality.