Iranian Journal of Accounting, Auditing and Finance
Volume:2 Issue: 3, Summer 2018

The purpose of this study is to provide an answer to the claim made by Stern Stewart & company that EVA is a superiority metric than traditional accounting measures in explaining stock return of a firm. This study was expressed to test the relative and incremental information content of EVA and profitability ratios like return on assets (ROA), return on equity (ROE), and return on sales (ROS). It covers 395 non-financial companies listed in the main market of Bursa Malaysia from 2006 to 2015. For empirically testing the hypotheses, panel data regression was used. Our finding did not support the claim of EVA proponents of its superiority upon profitability ratios. The relative information content test revealed that profitability ratios namely ROA, ROE, and ROS outperform EVA in their relationship with stock return. Furthermore, the incremental information content test also indicated that EVA has minimal incremental information content with stock return compared to ROA, ROE, and ROS. In summary, the findings exhibited that EVA is a valuable performance measure in Malaysian context. Therefore, it is recommended to Malaysian firms for using EVA with profitability ratios in firm’s performance evaluation.

This paper aimed to examine the effect of financial crisis severity on the relationship between profitability and competitiveness of the market in the listed firms in Tehran Stock Exchange. For this purpose, competitiveness was evaluated in the market with special emphasis on the market share and the financial crisis severity as a continuous variable of the financial crisis and economic instability in the country with special emphasis on the inflation rate. The study sample consisted of 137 firms from 2013-2017. For hypothesis testing, regression model was used. Results showed that the effect of profitability and the financial crisis severity on the firms' competitiveness is significant and negative. Thus at 0.95% confidence level, financial crisis severity affects the relationship of firm profitability and its competitiveness in the market significantly.

The aim of the current paper is to examine whether the chief executive officer’s (CEOs’) decision-making power effects stock price crash risk. Using an index that encompasses CEO duality, ownership power and CEO tenure as the sources of CEO power and negative conditional return skewness to measure stock price crash risk, empirical findings sufficiently reveal that there is a significant and reverse relation between CEOs’ decision-making power and stock price crash risk. The results prove that among three determinant of CEOs’ decision-making power, CEO tenure provides the most significant impact on decision-making power. The paper reliably provides sufficient evidence of CEOs’ decision-making power implications and progressively expands the academic literature on stock price crash risk. These findings provide further insights on the importance of CEO power in driving stock price crash risk and emphasize that improving CEOs’ decision-making power mitigates stock price crash risk in the context of Iran as a developing country.

The main purpose of this research is to investigate the relationship between specific fluctuations, liquidity risk and stock returns in companies listed in Tehran Stock Exchange. This research reveals the importance of information such as special fluctuations and liquidity risk and their role in determining the additional return on portfolios of companies to assist decision making of actual and potential investors in the stock market. In order to investigate purpose of this research, quarterly financial information of 152 companies among companies listed in Tehran Stock Exchange during the period 2012-2016 was examined. After collecting the required research data, panel data was used to test the hypotheses. Also, Eviews software has been used to test hypotheses. The results showed that special fluctuations have a positive and significant impact on liquidity risk and stock return. In addition, results showed that no reliable evidence indicating the impact of liquidity risk on stock return was found at 95% significance level.

According to Article 141 of the Iranian Trade Act, if half and more of the company's capital is destroyed due to the losses, the corporate board of directors is obliged to typically call for the extraordinary general meeting of shareholders immediately to decide on the dissolution or survival of the company. Whenever they do not vote to dissolve, in accordance with provisions of Article 6 in this law, the company must sufficiently reduce its capital to the extent to which is tangible. Hence, along with the entrance of the company into Article 141 of the Iranian Trade Act, the continuity assumption of the company may confront with ambiguity. Such a specific situation enhances audit risk since auditors are in a state of ambiguity in which they are naturally supposed to be more diligent, particularly to properly examine continuity assumption. The current paper aims to examine whether under this circumstances auditors demand higher fees in Tehran Stock Exchange (TSE), thus all companies subject to Article 141 for at least one fiscal year during 2012-2017 are surveyed as the statistical society and the direct impact of this specific subject on audit fees is carefully investigated by panel data. Empirical findings reveal that our sample experiences a significant increase in audit fees during periods in which they have been included in Article 141 of the Iranian Trade Act, comparing to years they have been uncovered by this Article. This paper enthusiastically fulfills an identified need to typically discover one possible reason of enhancing audit fees in TSE and also expands the academic literature in this arena in a developing country- Iran.

The primary objective of this paper is to investigate the asymmetric effect of return on assets on the profitability of Tehran’s stock market corporates based on variance inequality model. This research aims to answer questions such as how much the return on assets is effective on the profitability of companies based on Leveraging effect (symmetric or asymmetric)? The investigation is focused on all companies which are registered to Tehran’s stock market from 2014 to 2017 as a statistical population. The variance inequality model is considered equations around the mean and around the variance and accordingly based on the around the mean equation with return on assets coefficient 0.32, company growth factor 0.56, capital structure factor 0.03 and the company size logarithmic coefficient 0.07, together have the positive effect on the profitability of petrochemical companies. Also, results show that the depreciation tax shield cost with the coefficient 6.16 is having an adverse impact on those companies. Moreover, the results of the around the variance equation of asymmetric effect (leveraging effect) on the return of asset validates profitability of petrochemical companies.

The purpose of this research is localization of a method for analyzing and predicting the Bankruptcy of companies at three levels (financial health, Bankruptcy and bankrupt). In the first step, using the Relief-F multi-class AI algorithm among 54 initial independent variables, and using information from 1488 companies-years during the period 2011-2016, the financial risk variables, working capital ratio, long-run debt ratio, asset flow ratio, the economic value added ratio, the ratio of non-executive managers, the ratio of current debts to equity, the ratio of debt to equity, corporate size, earning management were selected as important variables in the prediction of the three-level Bankruptcy situation, respectively. Using relevance vector machine algorithm, the Bankruptcy situation of companies is predicted in the coming year and next two years using MATLAB 2017 software. The results of the research indicate that in general, the predictive power of the relevance algorithm in nonlinear mode is much higher than in linear mode, so that in the nonlinear mode, using the relevance vector machine algorithm, we can determine the company's Bankruptcy with accuracy of more than 93% for the coming year and more than 86% for the next two years.