فصلنامه مطالعات تجربی حسابداری مالی
پیاپی 43 (پاییز 1393)

Company valuation methods have been improved by the knowledge-based economy. Significant gap between corporate market value and accounting book value had led to numerous researches in «unexplained value» or «hidden reserve». Even though there are few surveys on intangible assets in Iran، Empirical studies in advanced marketsdemonstrate the importance of these assets. This study aims to examine the relationship betweenintangible assets and corporate market value oflisted companies in Tehran Stock Exchange (TSE). For this purpose، the sample including 1468 observations (Year- Company) of listed companies in TSE over 2006 to 2011 has been collected and hypothesizes were tested using «Landsman''s balance sheet identity model». According to the findings، intangible assets are correlated with corporate market value. In addition، upward trend in recognizing the value of intangible assets has been seen. It is notable that، tangible assets have a dominant role in valuating listed companies in TSE with descending trend in explaining corporate market value.

This research compares regression analysis including cross section regression and pooled regression for test of functional fixation hypothesis. The Comparison of cross section and pooled regression in case of functional fixation hypothesis is done. The comparison includes some statistical measures like beta coefficients، F test and T test and model assumptions. The results reveal that in both of univariate and multivariate regressions، the results are same statically point of view for cross section regressions and pooled regressions. Of course numbers of mentioned measures are different but it is not significant statically.

Individuals are thought to make biased judgments under uncertainty, because limited time and cognitive resources lead them to apply heuristics like representativeness. Representativeness is the tendency of individuals to classify things into discrete groups based on similar characteristics. In order to measure the representativeness bias, we examine the relation between past trends and sequences in financial performance and future returns in Tehran stock exchange (TSE) between1380-1390. We also investigate the impact of consistent sequence of financial performance in future return. Finally, the study examines the effect of subsequent performance that confirms or contradicts past pattern of growth on the predictability of future returns. The study uses annual data consisted of 800 firms-year and 3200 firms-quarter. The main research methodology is portfolio study. This study calculates financial growth rates over two periods: one year (four rolling quarters) and five years (using annual data). Three accounting measures of performance are calculated: sales, net income, and operating income. The results indicate that the abnormal returns in one-year trend are significantly positive. But abnormal returns in the year after five years of high or low growth are statistically and economically insignificant. In addition, we find little evidence about the consistency or pattern of firm performance effects on expectations of future returns. Finally, the past trend and pattern of growth do not lead to predictable returns following subsequent performance that confirms or contradicts this past trend.

The aim of this research is to investigate the explanatory power of asset turnover (ATO)/Profit Margin (PM) model in determining of changes of operating income of listed companies in Tehran Stock Exchange. Dependent variable is ratio of changes of operating income to net operating assets in forward year that is used to measure the information content of ATO/PM model in identifying earnings management. In this study, we propose a simple diagnostic of earnings management that relies on the widely held notion underlying DuPont analysis that sales is a fundamental driver of a firm’s investment and income, and that net operating assets on the balance sheet and net operating income on the income statement should vary directly with sales. Moreover, we note that changes in ATO and PM in opposite directions could signal earnings management. Independent variables contain upward and downward EM based on ATO/PM model. Also, operating income to net operating assets ratio in current year, changes of operating income to net operating assets ratio in current year, to net operating assets to sale ratio in current year, changes of net operating assets to sale ratio in current year, changes of ATO, changes of PM, components of managed accrual items based on abnormal accrual items (Jones adjusted Model), and market value to book value were applied as control variables. Statistical population contains 133 companies during 2004-2011. The panel/pooled regression models exerted to testify research hypotheses. Findings indicate that ATO/PM model compared with Jones adjusted abnormal accruals items model is of less relative information content in identifying earnings management.

Ability of companies to identify potential internal and external financing resources is an important factor fortheir growth and improvement. Main objectiveof companies is to maximize their shareholders'' wealth، and capital structure is one of the effective factors for this purpose which requires optimal use of financial resources to create proper returns regarding risk taken by companies. Based on data derived from a sample of 157 companies listed on Tehran Stock Exchange (TSE) from 1383 to 1389، this study examined relationship between company characteristics and capital structure. Approach of this study is descriptive-correlative، and panel data statistical method was used to test the hypotheses. Test results showthatsize، tangibleassets، andbusiness risk of the company have a significant positive relationshipwithcapital structure; and growth opportunities of the company has a significant negative relationship with it. However، the results do not show any meaningful relationship between age and industry of the company and capital structure.

Transactions with related parties are factors reducing market value of the investment. Although all transactions with related parties are opportunistic، but the prevailing view is that these transactions influence risk and are important for investors. In fact، lack of knowledge about the nature of transactions with related parties، causes information asymmetry for shareholders and investors. Therefore، this study aims to investigate the relationship between related-party transactions and earnings forecast error as well as independent board members (proportion of non-duty members of the board) on the relationship between related-party transactions and earnings forecast error. To investigate this relationship، we selected 78 companies data listed on Tehran Stock Exchange between 1387 and 1391. Using Eviews، hypotheses were tested. The results indicate that the related-party transactions are positively and significantly associated with earnings forecast error. In addition، the results show that the independent board members have moderating role on the relationship between related-party transactions and earnings forecast error.

Bankruptcy is a challenge that especially in this highly competitive era، many companies are faced with. Therefore the analysis and forecasting of bankruptcy are vital، especially for investors. Accordingly، the present study aims to introduce two techniques which are based on Data Envelopment Analysis (DEA) to analyze and predict bankruptcy of the food companies which are listed on Tehran Stock Exchange. The study is descriptive- functional andassesses the models of bankruptcy analysis، and 58 Food Companies Listed on the stock exchange have been considered as statistical population. The study results show that the DEA-Discriminant Analysis model was 92% accurate in predicting the bankrupt companies and 70% accurate in predicting the successful companies while the DEA-Additive model was 70% accurate in predicting the bankrupt companies and 90% accurate in predicting the successful companies، so in total the DEA-Discriminant Analysis model is more accurate than the DEA-Additive model، and it is preferred.