فصلنامه دانش حسابداری
پیاپی 34 (پاییز 1397)

This study aims to examine the value relevance of operating cash flows disclosures (direct method versus indirect method) by the measurement view. The proposed hypotheses state that the division of information sets in the cash flows statement helps to raise the ability of explaining the value of a company. The main hypothesis, followed by two minor subhypotheses, has been tested by the rival models of price level versus return accounting, using the data of 208 companies accepted in the Tehran Stock Exchange in the years 2010-2015. Wald and Voung tests were used to test the hypotheses. Findings showed that the disaggregation of net operating cash flows into its main components (as it is theoretically possible) results in increase in the ability of explaining shares' price and returns of companies. Therefore, the empirical evidence from the Iranian capital market supports superiority of the direct cash flows method to the indirect method in terms of usefulness of decision-making.

This study examines the explanatory power of accounting information, including operating, investing and financing activities, in forecasting variations in GDP or economic growth. In this approach, GDP has been broken down into four main economic sectors (agriculture, services, oil, and industry and mining) to forecast economic variables. The large number of unknown impact factors, and the presence of non-linear relationships between accounting and economic data have led this study to use multiple combinations of artificial intelligence models of neural networks, genetic algorithms and particle swarm optimization. The results of the models over the years 2006 to 2016 showed that the hybrid model of neural network and particle swarm optimization (HANNPSO) has more accurate forecasting than the hybrid model of neural networks and genetic algorithms (HANNGA). The findings also showed that the effectiveness of operating activities, especially accounting earnings, in forecasting GDP is more than that of financing and investment activities. In addition, the results indicated that among the economic sectors, the relationship between accounting information and the industry and mining sector is considerably high. The main consequence of this study is the existence of effective link between accounting and economic information that must be included in the economic and financial decisions.

According to the statement of Tehran Securities and Exchange Organization (SEO), reporting important weaknesses of internal controls and designing an effective system of internal control are necessary in achieving micro and macro goals of company. This study investigates the effect of agency costs on the relationship between quality of internal controls and earnings management in the listed companies in the Tehran Stock Exchange (TSE). We used the data collected from 96 companies in the TSE, during 2010-2015, with totally 672 firm-years observations, and the regression panel data model. Results showed that agency costs moderate the relationship between quality of internal controls and earnings management. And there is inverse relationship between quality of internal controls and earnings management in the absence of agency costs. This inverse relationship becomes exaggerated, when there are agency costs. This is because quality of internal controls affects earnings management of companies by reducing agency costs.

Audit committee is one of the effective monitoring mechanisms to increase the quality of disclosure of the internal control system, which helps reduce the cost of representation. Hence, many researchers have argued that the existence of an effective audit committee can play effective role in improving the information system and in ensuring the credibility of the company's financial reports. Based on this argument, the present study examines the relationship between company's characteristics and the effectiveness of audit committee, regarding the approach of structural equation modeling. A sample of 147 companies listed in the Tehran Stock Exchange during the years 2013 to 2017 was selected. The effectiveness of audit committee (hidden variable) was measured by the observed variables of financial expertise, independence and size of audit committee, and the characteristics of the company (hidden variable) was measured by the observed variables of firm size, financial leverage, composition of the board of directors, institutional shareholders, profitability, liquidity , and company growth. After ensuring the correctness of measurement results and structural model, findings showed that size of company, financial leverage, composition of the board, shareholders, profitability, liquidity and company growth increase the effectiveness of audit committee.

The analysis of stock market is crucial in predicting future events, and the network analysis is one of the newest methods in the analysis of stock market. In the quantitative science literature, network analysis is new concept for macro viewing of the whole market. Quantifying the relationship between different units is the favorite issue in scientific studies in understanding complex systems. The purpose of this research is to analyze the ownership network of the companies in the Iranian stock markets. The data in the years 2011-2016 was collected and analyzed, using softwares PreMap and UCINET. Results indicated that the class structure overcomes corporates’ relations, and some companies, in comparison with others, are in better position. This better position provides faster access to the available resources. Also, for the companies in better position, the ability in access to information through the cluster of network members has increased. Furthermore, such an advantage has enhanced their power of influence in the stock market. Hence, it can be claimed these companies are key actors in the governing structure of the Iranian stock market.

The companies with low entropy of financial statements, due to lower information risk and investor confidence, have lower financing costs. These companies have more operational action in achieving optimal capital structure. The main objective of this research is to investigate the effects of entropy of financial statements on the adjustment speed of capital structure in the companies listed in the Tehran Stock Exchange, using the data of 154 companies in the period 2006 to 2016 (totally 1694 years-company). To test the hypotheses, the Generalized Method of Moments (GMM) was used. To estimate the adjustment speed of capital structure, the partial adjustment model was used, and to measure the entropy of financial statements, the entropy, the continuous entropy of Renyi and Shannon were applied. Findings indicated that the entropy factor of financial statements have inverse relationship with the speed of companies in reaching their optimal capital structure. The results showed that the rates of modification for the companies with high and low entropy are 59% and 72%, respectively.

Audit committee is one of the corporate governance mechanisms, and there is little evidence in its role and characteristics in risk monitoring and governance in companies. The aim of this study is to examine the impact of audit committee’s characteristics on corporate risk. In this study, the impact of two characteristics of audit committee, consisting of accounting expertise and independence, on the risk of companies was examined, using data from the companies listed in the Tehran Stock Exchange in the years 2013 to 2015, and the pooled data model. The risk was measured by stock returns volatility and generalized autoregressive conditional heteroskedasticity (GARCH) model. Results showed that accounting expertise and independence of audit committee have positive impacts on stock returns volatility as corporate risk.