Nowadays, financial markets in Iran have attracted the attention of many managers, investors and financial policymakers. Therefore, in order to make the optimal decision and reduce the risks in such a market, it is important to identify and analyze the network behavior of the financial markets at different times to obtain the optimal decision. The current study aims to answer the following research question; how is it possible to use the minimum spanning tree and hierarchical clustering in the network analysis of the Tehran Stock Exchange? The period examined was 2013 to 2018. The population consisted of all the companies accepted in Tehran Stock Exchange. The sampling was selected purposefully and contained the companies which had at least one trading day in the time span from the beginning of 2013 to the end of 2018. The stock of the investigated companies was considered as the vertexes of one graph and the coherent information criterion was considered as the weight of the edge. First, the minimum spanning tree of the graph was calculated. The results revealed that the stocks of DarooAbuReihan, DarooPakhsh and Alborzdaroo had a high influence on directing the prices of the other stocks. Furthermore, the results of hierarchical clustering classified the stocks of the companies into 8 clusters. This study presents a viewpoint about the modern method designed for the analysis of complex financial networks. Moreover, the study offers an analysis of Iran's stock market structure which can be the center of finance researchers and analysts' attention.
The companies with major customers can supply a considerable source of cash flows by selling a large portion of their products to them. Since the lack of purchase, loss, or bankruptcy of major customers can result in a significant reduction in cash flows in the company, thus the risk is the companies with major customers is higher than other companies. Thus, the present study aimed to investigate the effect of customer concentration on company risks. For this purpose, the effect of customer concentration on three criteria of stock price crash risk, bankruptcy risk, and employment risk was studied. The research sample included 127 companies listed in the Tehran Stock Exchange during 2011-2018. Multivariate regression models with panel data were used by the random-effects method to test the research hypotheses. The research findings indicated that customer concentration has a significant positive effect on stock price crash risk, bankruptcy risk, and employment risk. In other words, stock price crash risk, bankruptcy risk, and employment risk are higher in the companies where the concentration of major customers is higher.
As the capital market becomes more competitive, one of the topics that has attracted the attention of many financial researchers in recent years is the liquidity of corporate stocks that because of the dynamics it can create in corporate financing, it is of strategic importance. The purpose of this research is designing a Model of Comprehensive interpretive/structural Mechanism of Effectiveness of Stock Liquidity Tehran Stock Exchange Companies. The one-year study period 2018-2019 in both qualitative analysis and quantitative analysis was conducted with the participation of two members of the panel. In the qualitative analysis section, this research identified through the combination of Delphi and the analysis of three components of the operational mechanism, the structural/governance mechanism, and the investor/mechanism of trading mechanism in the form of the effective statement on stock liquidity. And in the Comprehensive Interpretive / Structural Analysis section, with the participation of four Stock Exchange brokers, members of the panel presented a model based on a spectrum of the most influential statements to the least effective stock liquidity statements. The results show that the Delphi analysis of 25 indicators identified early in the meta-synthesis, 7 Index Remove and 2 indicators have been merged for a total of 16 statements were approved. In the quantitative section, based on a comprehensive interpretive/structural analysis, it was identified that the increase in the number of trading transactions as the component of operational mechanisms was identified as the most influential factor in stock liquidity.
Investors pay special attention to risk criteria in assessing the status of companies. So companies can help attract investment by disclosing important risks. So, it is expected that risk disclosure through decreasing information asymmetric between managers and investors can reduce uncertainty and lead to an increase in the companies' value. This paper studies the impact of risk disclosure on firm value in listed companies on the Tehran Stock Exchange. We used Miihkinen (2012) model to calculate our risk disclosure index. Firm Value is calculated through Tobin's Q variable. The statistical population of this study is all companies listed on the Tehran Stock Exchange from 2010 to 2016. The final selected companies are 59. We find that corporate risk disclosure has significantly and positively impact on firm value. That is, as the disclosure of risk increases, so does the value of the company.
Investment is seen as one of the most important and influential factors in economic growth and development. It is directly affected by managers' approaches to decision-making because identifying the best investment opportunities to achieve ideal returns is one of the expectations that shareholders and stakeholders have of managers to reduce agency gaps. However, the emergence of managers' overconfident behavior as a foundation for psychological bias can deepen the agency gap due to overestimating project cash flows compared to their real values under inflationary conditions. This study aims to examine the effect of inflation uncertainty on the impact managerial overconfidence has on overinvestment. The statistical population consists of companies listed on the Tehran Stock Exchange (TSE). One hundred five companies were selected as the sample size by systematic removal sampling reviewed in 2011-2018. Due to its dichotomous dependent variable, this study uses probit regression to test the research hypotheses. The results indicated the significant positive effect of CEO overconfidence on overinvestment. It was also noted that inflation uncertainty strengthens the positive effect of CEO overconfidence on overinvestment. Based on these results, the CEO's decisions as a decision-maker in charge of any company, especially under inflationary conditions, can play a substantial role in future corporate investment levels. Thus, with an increase in behavioral bias, it can be assumed that the company will confront grave competitive challenges under economic conditions.
Considerable researches have been devoted to predicting financial distress by using financial ratios and there is a little knowledge about this issue and how report paragraphs and information may contribute to predict companies’ insolvency. The major purpose of this study is to explore the effects of audit report types, pre-opinion paragraphs, special emphasis paragraphs, and other explanatory paragraphs on financial distress among firms listed on the Tehran Stock Exchange. The research period is from 2011 to 2018 and the sample consists of 107 firms which are selected using a purposeful sampling method. Results of multiple regression analysis shows there is not any significant association between audit report type, the number of pre-opinion paragraphs, special emphasis paragraphs and other explanatory paragraphs with financial distress.