Profitability
Omid Tarast; Farzad Ghayour; Parviz Piri
Abstract
Financial scandals and crises observed in many countries as a result of the manipulation of financial reports have led to a loss of trust among investors and stakeholders in financial information. This lack of trust in financial reporting and the low quality of financial information flows can act as ...
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Financial scandals and crises observed in many countries as a result of the manipulation of financial reports have led to a loss of trust among investors and stakeholders in financial information. This lack of trust in financial reporting and the low quality of financial information flows can act as a deterrent to attracting investment. In the present study, data from 148 companies listed on the Tehran Stock Exchange over a 12-year period (2012-2023) were analyzed. For hypothesis testing, the collected data were classified into 11 distinct groups. To assess cosmetic earnings management related to the rounding of earnings figures across life cycle stages, Benford's Law was applied. The Chi-square test was used to compare the observed (actual) frequencies of earnings figures with the expected frequencies based on Benford’s distribution. The findings indicate that for both high- and low-audit-quality companies, across all three life cycle stages—growth, maturity, and decline—there is no statistically significant difference between the observed and expected frequencies. Therefore, the earnings figures in all examined stages conform to Benford's distribution and show no signs of cosmetic earnings management. Future research is encouraged to conduct similar analyses at the industry level and to incorporate additional audit quality indicators, such as auditor turnover, auditor tenure, and auditor size
Introduction
Investors, who are the economic pulse of the financial industry, seek to be fully and transparently informed about the developments and events occurring in business units. Benford distribution (1938) can be considered one of the tools used to evaluate financial reports.
Benford’s distribution is an analytical process that compares actual results with expected results to identify abnormal transactions. This distribution, also known as the first-digit law, is a type of empirical observation that states that the first digits in many numerical data sets are distributed in a specific, non-uniform manner. In other words, Benford’s distribution indicates that, for each digit position (from the first to the fourth digit), the probabilities of the digits one through nine are unequal, and lower digits occur more frequently than higher digits. Therefore, the probability of smaller digits appearing in the leading position is higher than that of larger digits.
The rounding of financial figures often occurs when the observed distribution of numbers deviates slightly from the expected distribution. Any manipulation of figures, if carried out deliberately, can be considered a self-serving behavior, although such actions may serve the interests of the business unit or certain individuals. In view of the above, the purpose of this study is to investigate the extent to which profit figures of firms listed on the Iranian stock exchange are trimmed to achieve rounding aligned with managers’ personal interests. In line with the objectives of the research, the following questions are raised: Does high or low audit quality affect the extent to which profit figures are trimmed? Across the different life cycle stages under study, does profit trimming occur when audit quality is present or absent?
Literature Review
The Benford distribution was first introduced by Simon Newcomb (1881), an American mathematician who discovered a pattern in logarithmic tables. At that time, academics did not pay attention to Newcomb's research, and it was not until Frank Benford (1938), a physicist at General Electric, that this phenomenon was revisited and formally examined. Benford examined a set of natural data (20,229 randomly selected observations) such as baseball statistics, death rates, stock market prices, atomic weights in chemical compounds, Fibonacci numbers, river lengths and lake areas, urban population and census data, books and magazines, and similar datasets. Finally, he confirmed the distribution observed by Simon Newcomb, showing that in numerical data, there is a tendency toward smaller leading digits, and the repetition of the digits one and two is more frequent than that of the digits eight and nine. Following increased academic interest, this distribution was officially named and became known as the Benford distribution. However, research in this area did not progress as expected until Roger Pinkham (1961), a professor of mathematics, provided a mathematical proof of this phenomenon. Subsequently, the American mathematician Hill (1995) theoretically demonstrated, using a form of the influential central limit theorem in statistics, that the first digit follows this principle (Benford distribution). Based on his studies, Hill found that if the distribution of digits occurs randomly and random samples are extracted from that distribution, the resulting distribution will converge toward the logarithmic distribution (Benford's law), which can also assist in the interpretation and prediction of digital patterns.
Motivations related to profit embellishment in Iranian business units may differ from those in Western countries (Pourheidari and Hemmati, 2004). In studies conducted by He and Gan (2014) on the financial reports of Japanese business units, they found that applying Benford's law to profit and income accounts revealed that profit embellishment differs across industries, and that profit embellishment is more pronounced than income embellishment. In a study by Lennox et al. (2018), the authors examined profit embellishment, auditor adjustments, and the financing of business units, focusing on the magnitude of auditors' profit adjustments during financing events. They found that in the pre-financing stage, the magnitude of auditor adjustments that reduce reported profits is significantly large.
Methodology
The present study can be considered an applied study in terms of its purpose. The information was extracted using a purposive sampling method. This study seeks to design a model based on empirical observations, and the data used in the study are quantitative. The present study seeks a general result; therefore, it is both deductive and inductive in terms of the type of reasoning and conclusion. The present study covers all business units listed on the Tehran Stock Exchange during the period from 2012 to 2023, and accordingly, the final sample was selected using the systematic elimination method.
Results
The first main hypothesis states that the life cycle stages (growth, maturity, and decline) have a significant effect on the utilitarian neatness of the profit figures of business units. To test this hypothesis, given that it must be examined across three stages (growth, maturity, and decline), the analysis was conductedseperately for each stage. The first sub-hypothesis states that in the growth stage, there is no neatness in profit figures, and the distribution of companies' profit figures follows the Benford distribution. The results of the first sub-hypothesis indicate that the significance level for the second digit of profit figures is less than 0.05. Therefore, the null hypothesis, which states that there is no significant difference between the actual (observed) frequency and the expected frequency, is rejected. The significance level for the first, third, and fourth digits of profit figures is greater than 0.05, indicating that there is no significant difference between the actual frequency and the expected frequency. In addition, the test statistic for the second digit is higher than those for the first, third, and fourth digits. Therefore, the first sub-hypothesis is accepted.
Discussion
The results obtained from the hypothesis tests indicate that these findings differ from those of studies conducted in other parts of the world. Although the results of the current study indicate a lack of order in the profit figures of units listed on the Tehran Stock Exchange during the period from 2012 to 2014, it is not possible to state with complete certainty that there is a lack of order in these companies, as this phenomenon may manifest differently across industries and to varying degrees.
Conclusion
The existence of a phenomenon called rounding in the profit figures of business units during their life cycles is not supported by the Chi-square test. The results obtained indicate the absence of profit tidying by management in the profit figures of the sample under study. The results of the research also show that audit quality (high and low) has no effect on the presence or absence of tidying, and that no tidying is observed in the profit figures across different stages of the life cycle.
Accounting and various aspects of finance
Zahra Yousefzadeh; Gholamreza Mansourfar; Farzad Ghayour
Abstract
Today, with rapid and sustained changes in business markets, a growing number of companies have turned diversification into new product segments or global markets by shifting their business to increase the importance of long-term financial viability and sustainability. Moreover, increasing the variety ...
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Today, with rapid and sustained changes in business markets, a growing number of companies have turned diversification into new product segments or global markets by shifting their business to increase the importance of long-term financial viability and sustainability. Moreover, increasing the variety of products, covering the uncertain demand of customers, managing inventories and timely action have been important issues in manufacturing companies. Accordingly, the main purpose of this study is to investigate the impact of diversification strategy on inventory performance, which is one of the topics of operations management by considering the classification of the diversity into related, unrelated and international. The statistical population studied includes all companies listed in the Tehran Stock Exchange during the years 2009-2018. Sampling has been done by screening method, and the number of companies in the final sample has reached 120 companies. The hypotheses have been tested by the estimated generalized least squares method. The results show that related and international diversification have positive and significant effects on inventory performance. The findings also indicate that unrelated diversification has an adverse effect on inventory performance, but this relationship is not statistically significant. Based on the acquired results, an increase in related and international variety of products, relying on higher safety stock, has led to an increase in sales. In addition, the insignificancy in the effect of unrelated diversification on inventory performance can be attributed to production costs and marketing programs of manufactured products.
Gholamreza Mansourfar; Farzad Ghayour; Shabnam Khaleghparast Athari
Abstract
The purpose of study is to investigate comparative ability of accountinginformation to predict indices volatility of companies listed in Tehran StockExchange using intelligent methods including Support Vector Machine,Artificial Neural Network and classic Logistic Regression model. Sample ofstudy includes ...
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The purpose of study is to investigate comparative ability of accountinginformation to predict indices volatility of companies listed in Tehran StockExchange using intelligent methods including Support Vector Machine,Artificial Neural Network and classic Logistic Regression model. Sample ofstudy includes 91 companies listed in Tehran Stock Exchange that have beenclassified in 9 industrious groups during time period of 2003-3013.Considering 11 corporate financial variables, study results show that despitepredicting ability of around 60% by Support Vector Machine and ArtificialNeural Network, there is significant difference between actual and predictedresults. Classic Logistic Regression model also can explain only 4%industries’ indices volatility using selected 11 corporate financial variables.Finally, although intelligent methods are superior to classic methods,accounting information solely are not well-explainer variables for predictingindustry index volatility and variety of variables such as financial, political,economical are effective in predicting industry index volatility.
Abstract
The purpose of the study is to investigate comparative ability of accounting information to predict indices volatility of companies listed in Tehran Stock Exchange using intelligent methods including Support Vector Machine, Artificial Neural Network and classic Logistic Regression model. Sample of study ...
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The purpose of the study is to investigate comparative ability of accounting information to predict indices volatility of companies listed in Tehran Stock Exchange using intelligent methods including Support Vector Machine, Artificial Neural Network and classic Logistic Regression model. Sample of study includes 91 companies listed in Tehran Stock Exchange which have been classified in 9 industry group during time period of 2003-3013. Considering 11 corporate financial variables, study results show that despite predicting ability of around 60% by Support Vector Machine and Artificial Neural Network, there is significant difference between actual and predicted results. Also, classic Logistic Regression model can explain only 4% industries’ indices volatility using selected 11 corporate financial variables. Finally, although intelligent methods are superior to classic methods, accounting information solely aren’t well-explainer variables for predicting industry index volatility and variety of variables such as financial, political, economical … are effective in predicting industry index volatility.
