جستجوی مقالات مرتبط با کلیدواژه « بازده » در نشریات گروه « حسابداری »

The main objective of this study is to investigate the impact of auditor distraction to the audited companies in shock on Audit quality.

The sample consists of 103 firms listed in Tehran Stock Exchange during 2017 to 2022, which are selected using the systematic removal method. In this research, the audit quality has been measured by using two criteria of beating earnings forecast and earnings restatement. Finally, the hypothesis of this research was tested through logistic regression using Eviews software.

Results of the study indicate that clients of distracted auditors are more likely to meet earnings forecasts or the actual earnings per share will be geater than earnings forecasts (beating earnings forecast) and also, clients of distracted auditors exhibit a higher probability of restating their earnings in subsequent years.

Overall, auditor distraction to the audited companies in shock reduces the audit quality.           

Contribution: 

Considering the impact of the auditor distraction on audit quality, it is very important to pay attention to the quality of auditors’ report in preventing their clients’ opportunistic financial reporting.

In recent decades, the frequency and intensity of extreme weather events have increased in many parts of the world, including our country, as a result of global warming. This study examines the impact of weather disasters on the stock market of Iran. A combination of accounting ratios and statistical tests are used to estimate the effects of extreme weather events on the stock market and index of different market groups. To achieve the purpose of the study, the time-series data of the period 2010-2024 have been used. The results showed that the negative impact of weather disasters on stock market returns and volatility is observed one day after the extreme weather events. This effect can be seen in most market groups. The insurance and pension group and the banks group are the most affected, while the basic metals group is the least affected by the studied weather events.

This article models the long-term performance of initial public offerings. For this purpose, the monthly data of 236 IPOs in the Iranian financial market during the years 2009 to 2021 have been selected and modeled by a combined approach in the stepwise method. At first, Modeling was done for 12 periods (including periods of 3 to 36 months) and then by analyzing and comparing the results, the most suitable periods were selected to explain the long-term performance of IPOs. The results showed that the return of the portfolios formed by initial offerings can be explained at a suitable level, and the main factor in explaining the return is market premium, and the profitability and its distribution ratio are also significant factors in explaining the return of initial offerings. The most suitable periods for use as a long-term period were determined as periods of 12, 21 and 27 months.. .

In this research, the individual's response to the outcome of his behavior (investment in the stock market) is measured in the form of the corresponding inference theory (Attribution theory), In fact, this theory considers that what factors do people attribute to the outcome of their behavior (investment in the virtual stock market). This assessment was carried out in a quasi-experimental way on a number of people who were alike in terms of knowledge of investing in the exchange, in three steps. The results indicate that when people get negative returns, they attribute it to external factors; and, conversely, when they achieve positive returns, they attribute the result to their intrinsic qualities. These two results are in fact consistent with the concept of the theory of the corresponding inference (Attribution theory), and in some way, confirm this theory in practice.

The company's performance is influenced by various factors that have a great impact on their success or failure. In this paper, we study the relationship between liquidity, financial leverage, sales growth and cost with price volatilities and stock returns on companies listed on the Tehran Stock Exchange. The research method is descriptive-correlational. It has also been post-event research since the historical data of companies has been used. The statistical population includes all companies listed on the TSE. The model has been examined on the financial statements of 123 companies during the period 2011 to 2017. Results show that there is a significant relationship between liquidity, financial leverage, sell growth and stock price volatilities. The adjusted coefficient for price volatilities and price returns are 0.207 and 0.368, respectively. Furthermore, the results show that the mentioned variables have a higher impact on stock returns than stock price volatilities.

The result of empirical research in the capital market indicates that the pricing of securities is such that those who are more risk-takers will gain more returns in the long run. So far, various models have been proposed to explain the relationship between risk and returns. In line with these models, the modified capital asset pricing model (MCAPM) as other pricing models and It is also proposed as one of the CAPM asset pricing models. Therefore, the present study attempts to examine the empirical test of this model in Tehran Stock Exchange, which shows that the MCAPM model has more explanatory power than traditional CAPM in relation to stock returns. In other words, adding a variable in the traditional model has improved.

In this study, with using of four algorithms: linear discriminant analysis algorithm, quadratic discriminant analysis algorithm, K-nearest neighbors algorithm and decision tree with the help of 16 independent variables has been addressing to predict stock returns and systematic risk. Four algorithms are running once with using of whole independent variables and one again with using of 4 independent variables that are known with using of filtering approach as the most effectiveness of variables in predicting the return and risk. Then the accuracy of forecasting 4 algorithms in both cases (in total, 8 predictions for return and 8 predictions for risk) compares and chooses the best algorithm. For this purpose data of 107 companies listed in Tehran stock exchange is used during the period of 2002 to 2014. The results show that in the case of using 16 independent variables, the linear discriminant analysis algorithm provides the best prediction for return and the quadratic discriminant analysis algorithm provides the best prediction for systematic risk. But in the case of using independent variables that are chosen, the quadratic discriminant analysis algorithm offers the prediction for return and linear discriminant analysis algorithm offers the best prediction for systematic risk. In general, using of selected independent variables (instead of using whole independent variables), improves the algorithm's ability in prediction of return and systematic risk.

Over the last decades, the behavior of stock return has been one of the most important and widely documented issues on capital markets. Based on Capital Asset Pricing Model (CAPM), the systematic risk was the unique explanatory factor of return differences among firms. However, the weaknesses of CAPM’s forecasting led to the idea that the securities pricing method is the result of an interplay of different variables. These abnormalities were also interpreted as the evidence of capital market inefficiency. In this regards, in the last decade of the twentieth century, studies by Fama and French showed that both the size and the book value to market value ratio of companies could better explain the differences between stock returns. Further researches also showed that other accounting variables have strength impact in explaining stock return volatility and they contain useful financial information. Hence, various models were proposed to assess factors, which affect the firms’ return. In the meantime, consideration of only one financial statement fails to take into account the role of information content of variables of the other financial statements. Thus, taking a comprehensive collection of information, including financial statements data and other external environment characteristics such as growth opportunities and stock turnover, would provide a more realistic perspective on the factors affecting return to decision makers. To this end, considering the overlap degree of variables, this paper aims to investigate the relationship between group and individual financial and accounting variables, and the return of publicly listed firms in Tehran Stock Exchange (TSE). Besides, the study attempts to identify the underlying factors that explain the common covariance of the variables that affect the return. Research Hypothesis: H1: There is a significant relationship between individual characteristics of listed companies in TSE and their returns volatility. H2: There is a significant relationship between combined characteristics of listed companies in TSE and their returns volatility. Data and Using systematic filtering, 113 firms from the period 2001 to 2009 of TSE were selected. Since most of the selected companies belonged to only “automotive” and “non-metal mineral” sectors, the analysis in industry level were performed among the mentioned two industries. Using univariate and the unbalanced multivariate panel data analysis hypotheses were tested in two levels and in each level, two specific questions were answered. Factor analysis utilized for the sake of multicollinearity problem between explanatory variables. Factor analysis is based on the same key elements that are sensitive to the covariance between the observed variables. The findings show that 14 out of 30 variables were significantly associated with the stock returns. The results of factor analysis indicate that “profit per share”, “current ratio”, “the ratio of sales to price” and “the traded market value to total market value” are the most effective variables, such that they are able to explain about 60 percent of average changes of the stock returns. Moreover, four econometrics models are proposed for predicting the stock returns of TSE. The results of individual effect of each explanatory variable on stock returns in the automotive industry show that 15 variables out of 30 variables were significantly associated with stock returns. Using factor analysis, four factors were extracted and they could explain about 75 percent alteration of stock returns. Based on the factor loading, the variables “EPS”, “Reten”, “LnMV” and “MVtrade” are the most effective variables in the factor scores. Furthermore, six models were obtained from factor analysis. The results of individual effect of each explanatory variable on stock returns in the non-metal mineral industry show 13 variables out of 30 variables were significantly associated with stock returns. In another stage, using factor analysis, four models obtained from factor analysis and the extracted variable could explain about 70 percent alteration of average stock returns. Based on the factor loading, the variables “EY”, “CFMtP”, “Grow” and “MVtrade” are the most effective variables in the factor scores. Discussion and The main objectives of this study were to investigate the relationship between "firm-specific characteristics" and stock returns as well as identifying the underlined factors, which express the common changes of correlated variables. Based on domestic and international studies, 30 variables as "firm-specific characteristics" were selected. Then the relationship between individual and grouping form of these variables and stock returns of 113 publicly listed firms of TSE during the period 1388-1380 were investigated. Besides, the analysis was repeated in industry level among “automotive” and “non-metal mineral” sectors. According to research results, the following recommendations would be presented to decision makers and especially investors. 1) In order to predict the future volatility of a variable, and for the sake of large sets of data collection, while considering all available information, especial attention should be paid to the underlined factors, which express the common changes of correlated variables. 2) Beside macroeconomic and financial variables, accounting variables should be taken in to consideration while doing analysis on future changes of capital markets and 3) Based on the comparative analysis and due to the instability of the variables that explain the variation of returns, rotation models are recommended to be used in factor analysis.

The present research was carried out in order to examine the effects of conservatism on the value of excess cash. In so doing, a sample of 100 companies listed in Tehran Stock Exchange during the years 2009-2013 was selected, and their data was analyzed. First, by examining the relationship between cash flow changes and the company stock returns, it was proved that the value of one Rial held in the company is less than one nominal Rial. Furthermore, in order to determine the effects of conservatism on the value of excess cash, the conservatism index was employed in the model of the study. It was revealed that by reducing the agency costs, conservatism resulted in an increase of the value of excess cash.

The Stock Market is Largely Influenced by the Flow of News and Information. In an Efficient Stock Market، Reaction of Investors to the News and Information appears to be a Correct Response. While in an Inefficient Stock Market، Reaction of Investors seems to be Overreaction or Underreaction. Neither in Overreaction nor Underreaction، Stock Price is being Defined Correctly. Through Overreaction modeling of Stock Market processed by Intraday OHLC Prices، which Refer to Open، High، Low، and Close Stock Prices، it is proven that Stock Market Price shows a Geometric Brownian Motion. Then Overreaction and Underreaction is shown to be identified through recognizing the Standardized Volatility Distribution. Furthermore، Discontinuous Flow of News and Information is introduced to extend the Model with more Realistic Assumptions. Two Statistics and Hypotheses are then organized in order to test the Overreaction into good and bad News; ultimately، to ascertain the Results not affected by the Heteroscedasticity، Hypotheses need to be tested again by the Modified Statistics.

The firm life cycle theory states that the enterprises have different risk characteristics in the different stage of the life cycle and pricing the firm factors by the capital market depends on the relative importance of these factors in different stages of the life cycle. The subject examined in this study is that whether the life cycle stages caused the different capital market reaction to risk factors? And if there is a convergence between the changes in the life cycle stages and risk factor relations? Common risk factors examined here are book value to market value, beta, size and financial leverage. The statistical universe of this study is the nonfinancial firms in Tehran Stock Exchange during the years 1383 to 1389. These enterprises firstly divided into three groups of growing, mature and declining ones by using the sales growth variables, change in capital expenditure and the firm age. The estimated regression model is a combination of the risk factors and performance with stock return which is adapted from the Arbitrage Pricing Theory. These results show that the capital market isn`t pricing the risk factors equally and the value relevance of the risk factors depends on the firm life cycle. Also the Cramer test results show that there is a significant difference between the risk factors` adjusted R-squared of the enterprises in the growth and decline stages with the mature ones. But this difference does not exist between the enterprises in growth and decline stages.

Maximizing of wealth or better say, end of period expected utility is the main goal of investors. But because of uncertainty of price changes, investors act in an unsafe environment and any risk reduction will redound to decreasing in expected return. Because of this, determining of the best measure of risk is so important in finance. There are many measures to quantify risk of investment. In this paper, we compare some of these measures of risk based on their ability to predict return in various time horizons. Therefore, four measure of risk (standard deviation, mean absolute deviation, semi standard deviation and value at risk) are selected from common and downside risk family and their abilities to forecasting return in one, two and three months periods are examined. Our analysis method is panel regression and results are conducted based on R-squared and nested regressions method. Our sample contains 66 Tehran Stock Exchange listed companies in time period of 1383 to 1387. Our results depict that semi standard deviation and value at risk have a better performance especially in one month prediction.

The main subject of this research is examining and analyzing the relationship between accounting earnings and stock returns based on firm size and life-cycle in companies listed in Tehran stock exchange. Earnings per share and change in earning variables were considered as independent variables, while stock return rates were selected as dependent variables. In addition, firm’s life-cycle and size were examined as control variables. In this research, data from during 1383 to 1387 were examined. In order to examine the validity of the research hypotheses, the Cross-Sectional data was employed. Results show that firm’ s size and life-cycle variables influence the relationship between earnings and returns and trigger an increase in the adjusted R2.

This paper provides evidences about existence of income smoothing and earning management in the Tehran Stock Exchange. In this study for earning management identification, we divided firms into two groups: smoothing firms and non-smoothing firms. Also the univariate analysis and logistic regression analysis used to test the research hypotheses. The results from univariate analysis show, that in the levels of net income and operation income, firms with weaker performance and in the levels of net income and earning per share, firms with more growth and also in the level of net income, firms with larger size and finally in the level of earning per share, firms with higher dividend pay out ratio, do management earning. Also the findings from logistic regression analysis indicate that firms with more growth and less returns do management earning.

In this paper, we will intend to introduce a new model of capital asset pricing model which is called Revised Capital Asset Pricing Model. First we calculate degree of economic leverage. We investigate five economical variables (Inflation rate, financial expenditure, unemployment rate, exchange rate and export) for calculating DEL. Then by combining Capital Assets Pricing Model with leverages (financial, operational and economic leverages), we found a new model which in title Revised CAPM (R-CAPM) and compared the model with traditional CAPM, Downside capital asset pricing model and Adjusted capital asset pricing model. We compared these models through experimental testing, for the case of 67 firms listed on the stock exchange of Iran for the period 2000-2007. For testing the research hypotheses, liner regression, Friedman and Wilcoxon Test is used. After theoretical conceptual studies, it was confirmed that there is a meaningful difference between measures of the R-CAPM expected return and the other models expected return. The best model which can use for predicting expected return in Iran stock exchange market is R-CAPM.

This study has been provide information regarding the impact of the selective strategy applied Companies (cost management strategy and product differentiation strategy) on their financial performance. Cost management strategy says that managers must do some works to buying, producing, sales and caring in the better forms of competitors. In different ways companies that use differentiation strategy can use it with best and different products. By using this strategy companies can increase price of products. The goal of this research is knowing the influence of cost management and differentiation strategies on Stock Exchange of Iran in different industries. We use the information of 45 companies accepted in Stock Exchange of Tehran from 1379 to 1389. The results show that both strategies have efficiency in stock return. Also we understand that differentiation strategy have the better effect on firms performance because in short time can not uses with another companies.