مجله پیشرفت های حسابداری
سال سوم شماره 1 (پیاپی 60، بهار و تابستان 1390)

Liquidity is an important issue for securities traded in financial markets. A certain level of liquidity is necessary for securities to be traded in the quantites required in a timely fashion whithout any price discount. The goal of this paper is to examine the relationship between different liquidity proxies and stock's trading characteristics for listed companies in Tehran Stock Exchange. In this paper, five different liquidity proxies are introduced. The proxies are stock turnover, the illiquidity ratio, zero return measure, proportional bid–ask spread and turnover adjusted number of zero daily volumes. Stock's trading characteristics include stock price, trading volume, return volatility, absolute return, and Beedle's thin trading measure. The efforts are significant as liquidity plays an important role in asset pricing, and the selection of liquidity proxies in a research design would have considerable influence on empirical results. Research hypothesis: The underlying principle in the relationship between liquidity and stock characteristics is based on order execution and inventory control (Stoll, 2000). Large trading volume reduces the risk of carrying inventory for a period of time, which should increase stock liquidity. Higher return volatility increases the risk of holding inventory, and it should have a negative effect on stock liquidity. Stock price controls the effects of price discreteness and can be used as a proxy for risk, as low price stocks tend to be riskier. Absolute stock return can be treated as an alternative measure of volatility. The advantage of this measure is that it is simple to calculate, particularly in comparison to conventional volatility measures. Similar to volatility, absolute stock return should have a negative influence on liquidity. A thin trading measure proposed by Beedles, Dodd and Officer (1988) is used to create a crude proxy for the proportion of missing daily returns. Since the Beedles measure aims to capture the thin trading aspect of stock illiquidity, it should be negatively related with liquidity. Thus, out testable hypotheses are: Hypothesis 1: Price per share is expected to be related to liquidity. Hypothesis 2: Trading volume is expected to be related to liquidity. Hypothesis 3: Return volatility is expected to be related to liquidity. Hypothesis 4: Absolute return is expected to be related to liquidity. Hypothesis 5: Beedle's thin trading measure is expected to be related to liquidity. This research is of descriptive-correlative type. The study sample includes 38 companies listed in Tehran Stock Exchange. The analysis in this paper is carried out at the monthly level from January 2003 to September 2009. For hypothesis testing, this study uses multivariable regressiones for pooled data. The variables being considered are liquidity proxies as the dependent variable and Stock's Trading Characteristics as independent variables.This paper employs five widely used liquidity proxies that are stock turnover (TO), the illiquidity ratio (ILLIQUID), proportional spread (PBA), the zero return measure (ZERO) and turnover-adjusted number of zero daily volumes (LM). Each is discussed in turn below:TOi,t = voli,t / sharei,t Where voli,tis the total trading volume for stock i in month t and sharei,t, t is the number of shares outstanding for stock i in month t. where is the return for stock i on day d in month t, and vi,d,t is the trading volume for stock i on day d in month t and D is the number of daily observations for stock i in month t.Where is the daily closing ask (bid) prices for stock i on day d in month t and D is the number of daily observations for stock i in month t.ZEROi,t = zeroreturni,t / tradingdayi,t Where zeroreturni,t is the number of zero daily return days for stock i in month t, and tradingdayi,t is the number of trading days for stock i in month t.Where is the number of zero daily trading volumes for stock i in month t; is the stock turnover rate for stock i in month t. is the total number of trading days in the market in month t. The trading characteristics include PRICE (price per share at the end of each month), VARIANCE (return volatility of daily stock returns in each month), VOLUME (trading volume aggregated in each month), (ABSR) Absolute monthly stock return and Beedles that is defined as:BEEDLES = {100 – [100/(n + 1)]}/100 Where n is the difference in time (measured in days) between the last price date and last trading date in each month. This paper examined the influences of trading characteristics on stock liquidity. Consistent with the literature, trading characteristics are important determinants of liquidity. In general the impact of the trading characteristics on PBA and LM is consistent with our hypotheses. However, their relationships with stock turnover exhibit a somewhat different pattern than the other liquidity proxies.This result suggests that the source of the stock turnover is not related to stock characteristics that are important for the other proxies. Notably, we have been silent on the question of what is the “best” liquidity proxy. This research issue is beyond the scope of the current study. However, as noted in Goyenko et al. (2009), the selection of liquidity proxies in an empirical design depends on what exactly one wants to capture. Our results support their assertion, as liquidity is multidimensional and can be captured by differentmeasures of trading activity. The current study shows that through firm trading characteristics, we can better understand the sources of liquidity.

Based on information approach, earnings concept indicates output of economic activities; however, as an essential criterion it is suspicious. Actual accounting has given considerable right to managers in determining of the earnings during different periods. In fact, based on this accounting system type, the managers have mass control on time recognizing some of the revenue and expense items. This subject causes an event named earnings management. Earnings management is the process of taking wise steps within the limits of GAAP to achieve the expected earnings. Optional acts of the managers by earnings management may provide the background to hide real value of assets and financial position, and create negative outcome for stockholders, employees, society, managers’ and their joy security. On the other hand, social responsibility pays attention to ethical subjects with relation to behavior and decision making of the company about subjects such as human resource management, environmental sponsor, occupational health, social relationships, and the relation to customers and suppliers. Taking part in social responsibility activities, not only improves the stockholders’ satisfaction, but has a positive effect on company’ credits, that is, the disclosure on company’s social responsibility creates a favorite picture of company among the stockholders. Earnings management behaviors may threaten the stakeholders’ interests, so, it’s expected the managers that manage earnings consider the social responsibility more because of satisfy action of the stakeholders. This study investigates the empirical relationship between earnings management and company’s social responsibility using data from the Tehran Stock Exchange. Research Questions or Hypothesis Inthis study our hypotheses are: H1: there is a significant relationship between social responsibility and earnings management of listed companies in TSE. H2: there is a significant relationship between company performance and earnings management of listed companies in TSE. H3: there is a significant relationship between company performance and social responsibility of listed companies in TSE. H4: social responsibility side by side with to earnings management behaviors has a deductive effect on performance of listed companies in TSE. H5: there is a significant relationship between organizational commitment and earnings management of listed companies in TSE. H6: there is a significant relationship between organizational commitment and performance of listed companies in TSE. The empirical methods used include multiple regression models, correlation tests, and Granger causality tests. Findings show that there is a negative relation between corporate social responsibility and earnings management, and 16% of CSR variation is affected by company size, financial resources and EM, adversely. Too, Corporate Financial Performance (CFP) has positive relation with EM and has negative relation with CSR, but CSR mid EM reduces adverse effect of CSR on CFP, and improves Financial Performance. Organizational commitment has negative relation with EM and CFP. Discussion and Findings revealed that the earnings management of social responsibility had less stability during research period. Indicating that the earnings management is affected by factors other than CSR. Iranian managers do not use CSR as a shield for EM subject or do not need to hide behind this shield, because attention to such responsibilities cause company performance reduction in short-time. Granger causality test shows that organizational commitment, company financial performance, and financial resources may be the cause of the earnings management in listed companies of TSE. The reason of deviation of the results of this study from foreign studies especially in investigating the relationship between earnings management and social responsibility, may be a lack of social responsibility and suitable knowledge of this subject among Iranian’ managers.

In accordance with modern financing literature, agency conflicts are considered as one of the determining factors of the capital structure of companies. In agency theory, increased use of liabilities in the capital structure of the company is introduced as one of the ways to reduce agency costs, as the increased use of liabilities in the capital structure of the company leads to decrease in conflicts of interest between managers and shareholders by reducing the need for financing through owner's equity. On the other hand, the results of several studies suggest that agency conflicts are considered as one of the determining factors of capital structure of the companies. Moreover, financing decisions, as one of the strategic decisions in managing companies, are influenced by the mechanism of corporate governance. Given the above, it can be concluded that the decrease in agency conflicts is related to financing through liability and there is also a relationship between financing decisions and agency costs and the mechanism of corporate governance. Hence, in this study, the factors affecting the capital structure of companies accepted in Tehran Stock Exchange are examined from the viewpoint of agency theory. Financing decisions of companies are complex processes and current theories, at best, can only explain certain aspects of diversity and complexity of financing choices. From management point of view, capital structure decisions are not only determined by internal and external factors affecting risk and control, but also values, goals, priorities and demands of management are very important inputs for financing decisions; In particular, financing decisions of the company are influenced by management conflicting incentives and manager's incentives for opportunistic actions can be influenced by corporate governance. On the other hand, it is argued that effectiveness of corporate investing decisions and the way of enjoying and using company's assets by managers in order to have more sales is also a factor affecting capital structure. Moreover, the results of previous studies show that profitability and growth are of effective factors on capital structure. Hypothesis: In order to achieve the objectives of this research, the following hypothesis are developed and tested: 1) There is a significant relationship between corporate governance and financial leverage. 1-1) There is a significant relationship between ownership concentration and financial leverage. 1-2) There is a significant relationship between the percentage of outside directors on the board and financial leverage. 1-3) There is a significant relationship between the duality roles of the CEO and chairman and financial leverage. 2) There is a significant relationship between agency costs and financial leverage. 2-1) There is a significant relationship between assets turnover ratio and financial leverage. 2-2) There is a significant relationship between the ratio of operating expense to sales and financial leverage. 3) There is a significant relationship between profitability and financial leverage. 3-1) There is a significant relationship between ROA and financial leverage. 3-2) There is a significant relationship between DPS and financial leverage. 4) There is a significant relationship between growth and financial leverage. 4-1) There is a significant relationship between Tobin’s Q ratio and financial leverage. The variables being considered are: book leverage and market leverage as the dependent variables, ownership concentration, the percentage of outside directors on the board, duality roles of the CEO and chairman, assets turnover, the ratio of operating expense to sales, ROA, DPS and Tobin’s Q ratio; and the control variables are assets structure, size and age of the company. In this research, 106 accepted companies in Tehran Stock Exchange, within the period 1383 to 1387 are investigated. For statistical analysis and to test hypothesis, the panel data regression are used. In this study, the factors affecting the capital structure of companies accepted in Tehran Stock Exchange was examined from the viewpoint of agency theory. The results obtained from examining these theories show that ownership concentration doesnt have a meaningful relationship with book leverage, but it has a positive meaningful relationship with market leverage which is in accordance with the study of Cespedes et al. (2009) and Fosberg (2004) and contrary to the results of Theis and Casey (1999) study. Also, the results show that the percentage of outside directors on the board and the duality roles of the CEO and chairman, according to Hassan and Butt (2009) and UgIurlu (2000) do not have any meaningful relationship with book leverage and market leverage. Contrary to Theis and Casey (1999) results, DPS doesnt have a meaningful relation with book leverage and market leverage. On the other hand, in accordance with Firth et al. (2000), natural logarithm of assets turnover ratio has a negative meaningful relation with book leverage and market leverage. There is a meaningful relationship between natural logarithm of the ratio of operating expense to sale and ROA and company's growth, and book leverage, but there is not any meaningful relation between these variables and market leverage. Reflecting on the obtained results, it can be understood that in both book leverage and market leverage, agency costs criteria are more than other variables.

The capital asset pricing model (CAPM) of Sharpe (1964) and Lintner (1965) was the most widely recognized explanation of stock prices and expected returns. It gives a prediction of risk of an asset or a portfolio and its expected return which thereby helps in evaluating potential returns of investments. Fama and French (1992) found that the cross section of average stock returns for the period 1963-1990 for US stocks is not fully explained by the CAPM beta and that stock risks are multidimensional. Two of these dimensions of risk, they suggest, are proxied by size and the ratio of book value of common equity to its market value (BE/ME). Fama and French (1993) came up with a model for explaining stock returns using three factors: market, book to market, and size. This model was supportive of Banz (1981) who claimed that ‘size effect’ was present for more than 40 years and that the CAPM was misspecified. Lakonishok, Shleifer and Vishny (1994) suggest that sorting firms on high and low B/M ratios exposes the investor to overreact in good and bad times. This cause them to over estimate stock prices for low B/M firms and underestimate them for high B/M firms, i.e. distressed firms. The ultimate result after the correction of the overreaction is high returns for high B/M stocks (value stocks) and lower returns for low B/M stocks (glamour stocks). This investor reaction leading to determination of stock returns is not explained by the CAPM. Hypotheses: In this paper, we investigate of factors affecting stock returns and profitability (such as size, beta, leverage, return of market and book-to-market equity ratio) among Irans’s listed companies in Tehran Stock Exchange using panel data. The hypotheses tested in this study are the following: Hypothesis 1: There is a significant relationship between Size and Stock Return. Hypothesis 2: There is a significant relationship between BV/MV and Stock Return. Hypothesis 3: There is a significant relationship between two variables Size and BV/MV with Stock Return. Hypothesis 4: There is a significant relationship between Size and profitability. Hypothesis 5: There is a significant relationship between BV/MV and profitability. Hypothesis 6: There is a significant relationship between two variables Size and BV/MV with profitability. Estimation We use panel data method to estimate the parameters of return and profitability. The panel data approach has several advantages compared to the cross-sectional approach often used in financial research. 1. Due to an increase in the number of data points, degrees of freedom are increased and multicollinearity problem is reduced thus the efficiency of econometric estimates is improved. 2. Panel data can control for individual heterogeneity due to hidden factors, which, if neglected in time-series or cross-section estimations lead to biased results. Heterogeneity is captured by firm specific fixed effects or random effects components based on the characteristics of the data set. Panel data follows a given sample of individuals over time, and thus provides multiple observations on each individual in the sample. Panel data combines the features of time series and cross-section. Panel data usually provides the researcher a large number of data points, increasing the degrees of freedom and reducing the collinaerity among explanatory variables; hence improving the efficiency of econometric estimates. Therefore two main models are tested: 1) the static panel data with fixed effect and 2) the dynamic panel data. However, the fixed effects model may give biased and inconsistent estimators because the error term may be correlated with the lagged variable. To deal with variables that may be correlated with the error term, we use instrumental variables. We use the Arellano and Bond (1991) two-step GMM (Generalized Method of Moments) estimator for our dynamic model which allows for heteroskedasticity across firms. The GMM estimator is consistent if there is no second order serial correlation between error terms of the first-differenced equation. Discussion of the This paper contains significant and consistent results. Using two variants of panel data analysis, we attempt to find the determinants of stock return and profitability in the Tehran Stock Exchange for the period 1381-1388. The results of testing hypotheses for each of the eight years and the pooled sample show that the size of companies, Beta and Returm of market are positively related to Stock Return. Lewllen (1999), Allen and Cleary (1998), Mukherji et al (1997), Barber and Lyon (1997), Fama and French (1992), and Chan et al (1991) found a positive and remarkably great relationship between BV/MV and the Stock Return. Surprisingly the findings of the research did not confirm the existence of any positive relationship between the two variables. This study also show that the size and leverage is positively related to profitability but book-to-market equity ratio is negatively correlated with it. This study suggests that there is no existence of a linear relationship between profitability and return of market.

Both accountants and financial economists and financial management have devoted considerable attention to the impact of governance structures. The accounting literature documents that these factors have a substantial impact on earnings management, while the finance literature shows that they likewise affect financial performance. Consistent with past research, our paper is similar to Black (2001) and Garay & González (2008), who tested the relation between corporate governance and firm value in Russia and Venezuela as transition economies characterized by weak investor protection. The evidence we show here adds to the growing literature worldwide that indicates that firms can differentiate themselves by adopting better corporate governance practices and policies. That is, even in a weak investor protection environment, firms can increase their market value by adopting good corporate governance measures. Hypothesis Corporate governance practice has positive relationship with firm and ownership characters. Methds: Most studies on firm-level evidence on corporate governance practices gather their information using questionnaires filled by the companies themselves. This methodology presents various potential problems, among others: a low response rate, especially from those companies whose corporate governance practices are poor (self-selection bias); and, for the firms that do respond to the questionnaire, there is a tendency to present themselves not as they are at the moment when the questionnaire is being completed, but as they want to see themselves in the future (self-report bias). In our paper we follow a different route to construct our CGS. In the same spirit of Garay & González (2008), we answer the questions ourselves using publicly available information. The Corporate Governance Score (CGS) was constructed based on 21 questions pertaining to different corporate governance practices. We answered these questions for each of the 125 Iranian firms that were listed in the TSE. The answer to each question is either “Yes” or “No.” If the answer is “Yes,” we add 1 and if the answer is “No,” we add 0. All answers are based on publicly available information. These 21 Questions were answered after reviewing each firm’s financial statements, bylaws, minutes of the boards of directors and shareholders’ meetings, and annual reports available at WWW.rdis.com. Results, discussion and Result show that role of non-executive managers is very weak in Iran and there is seemingly no concern about supervising organizational morality. The institutional stockholders have not been able to use their power utility and facilities to improve the governance indexes.

On the basis of theoretical principles of financial reporting, the primary goal of financial reporting is to assist the investors to make economic decisions. Economic decisions are related to optimal allocation of the resources. One of the most important decisions is related to investment in stocks which is itself considered as a function of the value of the investment seeking company. In its conceptual statement of financial accounting No. 1, the Financial Accounting Standard Board (FASB) announced the presentation of useful information to the investors, creditors and other potential and present users for assessing the amounts, timing and uncertainty of cash flow as one of the goals of financial reporting. In spite of the knowledge of FASB about the importance of the amounts contained in financial reports, it has presented little guidance on the manner of using these amounts in its conceptual statement. Therefore, in order to fill out this gap, valuation models based on accounting have provided guidance in this area (Barth et al, 2005: 312). Accounting valuation models by information in financial statements evaluate a company. In the collection of the financial statements, the earnings enjoys special position and within the framework of the accepted accounting principles and in the accrual accounting system it includes two parts of cash flow and accrual. Regarding the ability of the management in the application of different methods of accounting for distortion and adjustment of the earnings through personal drive by accruals and with regard to the existing empirical evidence in this area based on the information content of these items, it is reasoned that accruals can be taken into consideration as an index for the determination of the improvement or the bankruptcy of the company (Palepu, 2000). Therefore, study of the effect of the accruals and its components on the value of the company seems necessary to assist the investors for investment decision making. Research Questions or Hypothesis: In this paper the ability of aggregated accruals and its components in forecasting abnormal earnings and explaining value of companies have been evaluated. The main purpose of this paper is answering the question: "Does disaggregating accruals to its four main components and disaggregating abnormal earnings considering the sign of abnormal earnings improve forecasting abnormal earnings and explaining values of companies?" Four main components of accruals are change in receivables, change in payables, change in inventory and depreciation. For this purpose six hypotheses are compiled. For testing the research hypothesis three linear information valuation models based on the framework of Ohlson Model are used. Then, for each linear information model distribution of prediction errors is constructed. For each distribution, absolute percentage error is calculated and to assess the statistical significance of differences in prediction errors, means for absolute percentage error are compared. To estimate the models, we use financial information of 70 sample companies for the period of 1995 to 2008 and pooled data method. The results indicate that the aggregated accruals have power for decreasing prediction errors of company value and abnormal earnings. Furthermore, four main components of accruals can decrease prediction errors of abnormal earnings but can not decrease prediction errors of company value. These results hold both the general model and the disaggregated sign model. Another result of this paper indicates that aggregating abnormal earnings by its sign does not decrease prediction errors of abnormal earnings and company value significantly. Discussion and In general, it is inferred from the findings of the present research that in spite of the aggregated accruals in the estimation of abnormal earnings and value of company that not significantly improve forecasting abnormal earnings and explaining value of company. These findings are also true for the four components of accruals to explaining value of company. Additionally, the sign of abnormal earnings has no significant effect on the improvement of the prediction of abnormal earnings.

One of the basic problems of applied finance is the optimal selection of stocks by conflicting objective of maximizing future return and minimizing investment risk. The first systematic treatment of this dilemma is the mean variance approach proposed by Markowitz. Markowitz combined the optimization and probability theory to solve the dilemma. In Markowitz’s mean variance model, the security returns are assumed to be random variables, and the investors are postulated to establish equilibrium between the conflicted objectives, which the investment risk and return are respectively quantified by mean and variance of portfolio of security. A basic assumption behind Markowitz’s mean variance model is that the situation of the stock market in future can be correctly reflected by security data in the past, that is, mean and covariance of a portfolio of securities in the future are similar to the past ones. However, there are so many uncertain factors that this assumption cannot be guaranteed for the real ever changing stock markets. This uncertainty can be fuzzy variables, and consequently, a portfolio of securities can be selected on the assumption that security returns are considered to be fuzzy variables. A fuzzy variable is a measurable function from credibility space to a set of real numbers. Sometimes, fuzziness and randomness simultaneously appear in a system. A hybrid variable describes the quantities with fuzziness and randomness. A hybrid variable is a measurable function from a chance space to set of real numbers. A hybrid variable can be fuzzy random variable and random fuzzy variable. A fuzzy random variable is a measurable function from a probability space to a collection of fuzzy sets, and a random fuzzy variable is a function from a possibility space to a collection of random variables. Another Markowitz’s assumption is homogenous expectations that all the investors share the same expected returns and predicted variance and covariance about the future is unrealistic in real world. In this paper, λ mean variance portfolio selection model which assumes security returns are fuzzy random variables and considers the investors’ subjective opinions for estimating the rate of return of each security that is compared with Markowitz’s mean variance portfolio selection model assuming security returns are random variable, thus considering homogenous expectation for the investors. Research hypothesis: In this paper, we try to answer the question of “what differences are there between the efficient frontier of the λ mean variance portfolio selection model and Markowitz’s model?”. In order to compare efficient frontier of the λ mean variance portfolio selection model and Markowitz’s model, two hypotheses are considered as follows: Hypothesis 1: In a given level of portfolio risk, optimistic portfolio return is completely greater than Markowitz’s portfolio return and Markowitz portfolio return is completely greater than pessimistic portfolio return.Hypothesis 2: In a given level of portfolio return, optimistic portfolio risk is completely less than Markowitz’s portfolio risk and Markowitz portfolio risk is completely less than pessimistic portfolio return. Two types of data are collected in this research. First, the historical security returns are collected monthly from Tehran Stock Exchange with respect to the limitation that the company trading symbols remain open for 45 consecutive days from March 2005 to March 2010. Based on the limitation, the numbers of companies are obtained 63. Because of collecting questionnaires and receiving better answers from the quality aspect, 30 companies are selected considering simultaneously more mean of days which company symbols remain open and the more mean of monthly historical returns during the years. The second is the maximum and minimum expected returns which are collected by questionnaires. In this paper they are considered by experts who are the managers and staffs of the brokerage firms and investment companies. The brokerage firms and investment companies are 121 totally. Because some companies may not answer to the questionnaires, the estimation sample is applied to determine how many questionnaires must be collected. Finally, these data are used in the λ mean variance and Markowitz’s model to calculate risk and return portfolios. SPSS software program is applied to test the hypotheses according to analysis of variance (ANOVA). Because SPSS software is used for two tailed test, first, hypotheses 1 and 2 are examined as two tailed test, then, Tukey’s test is performed. Testing hypotheses showsis accepted and rejected. Considering the results of the hypothesis testing, the research question can be answered as Markowitz’s efficient frontier is under the optimistic efficient frontier and above the pessimistic efficient frontier.Conclusion and One of the fundamental assumptions behind the Markowitz’s model is that the future situation of the stock market can be correctly reflected by security data in the past, which future security return is calculated on the assumption that security return is random variable. The other basic assumption of the Markowitz’s model is homogenous expectation, that is, all investors share the same expected return. These problematic assumptions have been dealt with λ mean variance model on the following assumptions. First, security return is fuzzy random variable. Second, investors have heterogeneous expectation. In fact, investors use experts’ judgment according to left and right spread of security returns and select their subjective degree of optimism-pessimism. The result of the research indicating two new assumptions lead to Markowitz’s efficient frontier placed between the optimistic and pessimistic efficient frontier. Investigating how this research results in selecting appropriate portfolio requires more researches.