logistic regression

Financial statement information disclosed by companies is the main source of information for making investment decisions. Therefore, in this study, the role of the business environment on the possibility of fraud in the financial statements of 120 companies admitted to the stock exchange during the years 2017-2018 was investigated using the logistic regression approach. For this purpose, the effect of 31 variables on the possibility of financial statement fraud was investigated, of which 9 variables were related to the business environment and the rest were related to the corporate level. The results showed that the estimated logit model explains about 26% of the changes in the ratio of the probability of fraud in financial reports to its non-occurrence. Two variables of per capita income and free market exchange rate among the nine variables of the business climate have a significant effect on the possibility of fraud in the financial report of companies, and with a one percent increase in the per capita income, the probability of financial statement fraud decreases by 52 percent and with An increase in the exchange rate in the free market also increases the probability of fraud in the financial reports of the investigated companies by 43%. The results of the research show the importance of business environment variables along with company level variables in predicting the possibility of fraudulent financial statements of companies.

Independent auditing plays a fundamental role in improving users' decision-making and market efficiency through validating financial reports. The quality of the work of these auditors depends on several factors, one of the most important of which is their independence. Since the phenomenon of auditor change is related to independence, this phenomenon, which is considered one of the vital issues of every company, should be carefully examined. The phenomenon of auditor change creates a break between auditors and the employer. Predicting the continuation or termination of the relationship between the auditor and the client in the coming years is one of the challenging issues in the field of auditing. In this regard, the purpose of this research is to predict voluntary auditor change (non-continuation of the relationship with the current client) using a meta-heuristic algorithm (Water Cycle Algorithm, WCA) and to compare the results with the logistic regression method.

The statistical sample is 185 companies listed on the Tehran Stock Exchange, selected by the systematic elimination method from 2017 to 2023, and their information was collected. Years with mandatory auditor switching are excluded. Then, Excel and Matlab software were used for implementing methods and predicting auditor change. Thirteen financial and non-financial variables that were extracted from the literature were used to predict auditor change in this research. These independent variables include: current ratio, working capital, debt ratio, asset ratio, return on assets, earnings quality, firm size, audit firm size, auditor opinion type, management change, separation between CEO and the chair of the board of directors, accounting conservatism, and firm competition power. Moreover, using the confusion matrix, which includes 4 evaluation criteria: accuracy, precision, sensitivity, and specificity, the results obtained from the Water Cycle Algorithm were compared with the results of logistic regression, a prominent method for forecasting binary variables such as auditor change. Additionally, these algorithms were run 10 times to ensure the reliability of the results.

In almost all implementations and based on all 4 performance evaluation criteria, the Water Cycle Algorithm is more suitable than logistic regression for predicting auditor change. In general, the criteria of accuracy, precision, sensitivity, and specificity in predicting the change of auditor using the Water Cycle Algorithm were 89%, 75%, 2%, and 99.9%, respectively. In comparison, the logistic regression criteria were 67%, 74%, 1%, and 99.8%, respectively

The Water Cycle Algorithm can be useful for predicting voluntary auditor changes by users and auditing firms. Audit institutions can use this tool to predict the continuation or non-continuation of their relationship with clients in the coming years and better plan to maximize profitability. Audit clients and companies can also use this tool to forecast future relationships with auditors and plan and schedule more efficiently for selecting the next auditor.

Tax is considered as the main tool for earning income for governments to achieve their economic and social goals. On the other hand, tax expenditures lead to the withdrawal of liquidity from companies and reduce stockholders' dividend, so corporate executives try to reduce or postpone their income tax. The purpose of this study is to Modeling for Identifying Effective Factors Affecting Tax Reporting Aggressiveness in Iran capital market. In this study, effective factors on tax reporting aggressiveness based on empirical studies, theoretical foundations and principal component analysis (PCA) method are divided into four financial, non-financial, governance and managerial indicators. In order to test the research hypotheses, 75 companies listed in Tehran Stock Exchange during 2008-2017 were surveyed. Since the dependent variable is a virtual variable, logistic regression and correlation methods have been used to estimate the model. The results show that financial indicators have no significant relationship with tax reporting aggressiveness, but non-financial, governance and management indices have significant relationship with tax reporting aggressiveness. Other findings indicate that sovereign, managerial, non-financial and financial indices have the most impact on tax reporting aggressiveness, respectively. Other findings indicate that governmental, managerial, non-financial and financial indices have the most impact on bold tax reporting, respectively.

Bankruptcy or business failure can have a negative impact on both the company itself and the global economy. In this research, the financial bankruptcy risk prediction of stock and transborder companies has been done using machine learning algorithms, Where the ultimate goal is to predict the financial bankruptcy risk of stock exchange and transborder companies. Collective learning is a field of machine learning in which instead of using a model to solve a problem, Use multiple models in combination to increase the output estimation power of the model. Each model is retrained using optimal features. As a result, the accuracy of predicting machine learning model by Stacking method, which is one of the strongest techniques of collective learning, To predict financial bankruptcy risk is higher than similar methods. Investors always want to prevent the deterioration of their capital by anticipating the possibility of a company's bankruptcy. Therefore, they are looking for ways to predict the bankruptcy of companies.

The effect of managers' overconfidence on the possibility of financial crisesIn this study, the relationship between the Managerial overconfidence and Financial distress like lihoood is examined. The research sample consists of 185 firms listed in Tehran Stock Exchange during 1389 to 1393 and in the period studied by systematic elimination method was studied. To review hypothesis of research, logistic regression model was used. The results of this study show that in the period studied, Managerial overconfidence and Financial distress likelihoood and there is a significant positive relationship. In other words, the Managerial overconfidence in firms is increasing the financial distress likelihood. In other words, Managerial overconfidence, increasing the Financial distress likelihoood in the firms. The effect of Managerial overconfidence, on the Financial distress likelihoood is significant at 95 percent confidence level. The results show that the life of the company depends on the ability of company managers and the satisfaction of a wide range of related groups of the companyKeywords: Managerial overconfidence, Financial distress likelihoood, Profitability Ratio, logistic regression

The main purpose of this study is to investigate the relation between auditor characteristics and probability of bankruptcy. This study uses variables such as auditor fees, audit-firm size, audit-firm tenure, and auditor industry specialization as auditor characteristics. Also the study uses Altman (2000) and Kordestani at el (2014) as bankruptcy Indices. Data collected from 98 firms over the period 2005-2015 are analyzed using logistic regression. The results indicate that there is no significant relation between the auditor's characteristics and the probability of bankruptcy obtained through Altman's model. On the other hand, findings show that firms which have higher audit fees and are audited by large audit firms are more likely to default (calculated by the Kordestani model). In addition, firms audited by long-tenured auditor firms and industry-expert auditors are less likely to go bankrupt. ‌

The purpose of the present study is to provide a model for predicting fraudulent financial statements and applying Benford law to listed companies in Tehran Stock Exchange. The research method is descriptive-survey and in terms of purpose, it is also applicable. The research data were collected from 2008-2018. The statistical sample of the study consisted of 410 years-company of fraudulent companies and 410 years-company of non-fraudulent companies. Logistic regression method was used to develop the model. The results show that given the accuracy rate of 64.6%, this model plays an effective role in detecting financial statement fraud. The results of T-test and Levon test in 35 independent variables showed that in 20 variables, there was a significant difference between the fraudulent and non fraudulent groups. In addition, the compliance and any possible manipulations of the Benford law were examined in four different cases, And the results are as follows: A look at the income statement figures and balance sheets in non-fraudulent companies showed that the Banford distribution correctly identified the fraudulent companies but identified the fraudulent companies as inaccurate. Consideration of the financial ratio of total assets to sales and the Days payable outstanding to fraudulent companies showed that the Bannford distribution classified these companies as fraudulent and correctly classified them, but assessed the non-fraudulent companies as fraudulent

The present study examines the effect of conditional and unconditional conservatism on the auditor's opinion in the companies listed in Tehran Stock Exchange. For this purpose, 87 companies were surveyed during the period from 2009 to 2014. In this research, the conditional conservatism was assessed by two Khan and Watts and Ahmad and Dolman criteria and Givoly and Hayn and Ahmad and Dolman criteria were used to measure the unconditional conservatism. The results of the study of the relationship between conditional conservatism and the auditor's opinion show that there is no significant relationship between conditional conservatism and modifying the auditor's opinion. On the other hand, based on the results of the study on the relationship between non-conditional conservatism,following Ahmad and Dolman's model and the auditor's opinion, it can be said that there is a significant negative relationship between unconditional conservatism and the auditor's opinion; in other words, by increasing unconditional conservatism, the possibility of offering modified opinion decreases.

Overconfidence is one of the most important personal characteristics of managers. Theoretically, Manager’s riskiness is directly related to this characteristic. The Possibility of unqualified opinion increases, if the auditor recognizes this personality trait of the managers and overestimates financial reporting risk due to Managerial Overconfidence. This study is aimed to determine the relationship between Managerial Overconfidence and Unqualified Audit Opinion in firms listed in Tehran Stock Exchange. This research uses the library research to collect theoretical basics and data and applies correlation method to test the hypothesis. The statistical population includes all listed companies in Tehran Stock Exchange and the sample consists of 66 companies during the period from 2007 to 2014. The logistic regression method is used to test the hypotheses of the research. The results show that Managerial Overconfidence has significant and negative relationship with Unqualified Audit Opinion. That means any increase of Managerial Overconfidence decreases the possibility of Unqualified Audit Opinion

Discussion of financial constraints is one of the major issues facing all companies. The prediction of financial constraints is an important phenomenon for investors, creditors and other users of financial information Companies with financial constraints provide lower cash costs at a higher cost. The cost of financing for firms with a financial constraint is higher.. This study uses 6-year financial data during 2011-2016 and using financial information of 288 years-company to study the factors affecting financial limitation and its prediction in Tehran's listed stock companies using the logistic regression method Paid. The results indicate the effect of fixed asset turnover, conditional conservatism, the ratio of operating cash to assets, firm size and stock price on the financial constraints among other proposed variables.

Today’s, bankruptcy and financial distress is one of the important factors for decision making process of market participants, so the need to predicting them with using a suitable model is the manifest of financial market analysts and investors because it have a significant effect on shareholder's wealth in the market. With such importance, the aim of this paper is to introduce a suitable model for predicting financial distress at Tehran stock exchange listed companies.For achieving this goal, thirteen variables including eight accounting and five market variables were used to determine financial distress with applying Logistic regression method from 2008 to 2016. For testing research hypothesis, the dates of 928 firm-year (522 distressed and 406 sound firm -year) was gathered listed in Tehran Stock Exchange (1040 firm-year).The results showed that a combination of accounting and market dates can predict distress in firms and can be a ground for further studies on financial distress.

This study aimed to investigate the effectiveness of capital market cycle on behavior of financial distress predicting patterns. In this study, the information of 211 distressed firms, selected by certain distress criteria, along with 211 healthy firms listed in the Tehran Stock Exchange in the period 2006-2015 have been used. The model estimation by the use of 35 selected indices in the two periods of capital market recession and expansion was carried out. In this study, Hodrich-Prescott Filter for determining capital market cycle and Logistic Regression and Support Vector Machine models for predicting financial distress were used.
The results showed that the behavior of financial distress predicting patterns are influenced by capital market cyclical variation in recession and expansion periods, but the influences are different in application of explaining variables and in predicting ability in the periods of recession and expansion. Also, the prediction ability in Support Vector Machine model is more than that in Logistic Regression model.

Accomplished researches in auditor's opinion type prediction emphasize the design of more sophisticated classifiers, and less feature (variables) selection and their appropriate methods. The Purpose of this research is investigating the usefulness of relief method in auditor's opinion type prediction of companies listed on Tehran Stock Exchange. To obtain comparable experimental results, Support Vector Machine (SVM) and logistic regression were used in this study. In overall, the experimental results of investigating 1214 firms-years in 2008 to 2015, confirmed the usefulness and positive effects of relief Method in predicting auditors opinion type. In other words, the application of this feature selection method, increases the mean of accuracy, and reduces the occurrence of type I and type II errors. Furthermore, the results indicated that SVM outperforms the logistic regression.

Abstract: Despite the importance of predictive variable in prediction, in most of the research in the field of auditors’ opinion the purpose was rendering the suitable models. Meanwhile, less attention was paid to the selection of optimal predictive variable and appropriate models of these selection. Therefore, in most of these research the predictive variables were chosen randomly and according to the prior research. The process of selecting variables could be used as a preprocess for omitting irrelevant variables and selecting optimal variables before creating the model. In this regard, this study investigates the usefulness of Correlation-Based Features Selection (CFS) in auditors’ opinion prediction of listed companies in Tehran Stock Exchange. The classifiers including Artificial Neural Networks (ANN) and logistic regression were used. In overall, the experimental results of investigating 1214 firms-years from 2008 to 2015, confirmed the usefulness of CFS Method in predicting auditor's opinion. In other words, the application of the CFS method, increases the mean of accuracy in comparison with using all variables, and reduces the occurrence of type I and type II errors. Furthermore, the results indicated that ANN outperforms the logistic regression.

The main objective of this study is to investigate the relationship between earnings management and managerial overconfidence in listed firms on the Tehran Stock Exchange. This study has attempted to answer the question as to whether that overconfidence from the chief executive officer can impact firm's earnings management. To answer the question of this study, we have investigated 915 year-firm observations from listed firms on Tehran Stock Exchange from 2004-2014. Data analysis and hypothesis testing was performed by using binary logistic regression. The results confirmed that as managerial overconfidence increased, then the earnings overstatement will increases. In addition, the results indicated that there is a significant and negative correlation between debt ratio and size of the firms with maximization of earnings management.

The purpose of this study is to classify customers of banking network on the basis of credit risk with anticipating models and multiple indicators decision making. Because one of the major factors in banking is credit risk, therefore, banks are interested in decreasing the credit risk using different methods. Descriptive data were randomly collected from 385 customer documents (250 individual customers and 135 company customers) of Melli Bank of Iran. The results indicate that both models of TOPSIS and LOGIT can be used in classifying good and bad customers by managers of credit institutes; however, TOPSIS model can better estimate than LOGIT.

Corporate governance is set of internal and external control mechanisms that establish balance between stockholders with needs and authority of board of directors. Poor corporate governance can increase the probability of corporate failure or bankrupt .The present paper aims to investigate the relationship between some mechanisms of corporate governance and bankruptcy. The purpose of this study, investigating relationship between some of corporate governance mechanisms with bankruptcy probability in companies listed in Stock Exchange. The research sample consisted of 115 companies, including 40 distressed companies and 75 healthy companies that is selected among companies listed in stock exchange at time period 1387-1392 and hypothesis testing is done using of logistic regression. In order to study the effects of simultaneous variables on the dependent variable, in addition to separate regression overall regression was estimated. Results indicate that among five studied mechanisms of corporate governance included type of audit's report, amount of board of director’s reward, institutional ownership and independence of board of directors are negatively related to bankruptcy possibility but no significance relationship between size of board of directors and bankruptcy possibility was found.

The purpose of this study was to investigate of the role of institutional ownership type the report of the independent auditors in listed firms in the Tehran Stock Exchange. In fact, this study seeks to answer the question whether institutional ownership (institutional investors) can play an effective role in type the report of the independent auditors, and if so, how this effect can be explained? To answer this question, the report of the independent auditors of the Auditing Standard No. 700 (revised in 2011 and in force since 20.03.2012 ), the two kind Un adjusted opinion (accebtable) and adjusted opinion (eventhal, rejected and no opinion) has been separated. The sample consisted of 111 companies listed in Tehran Stock Exchange during the period 2004 to 2013. To test the hypothesis has been used of " logistic regression analysis". The findings of this study suggest that among percent ownership investors institutional and possibility unadjusted audit report, there is a relationship positive and significant. The results also show that there is a relationship negative significant among level of institutional ownership concentration and possibility unadjusted audit report.

Overconfident managers might invest free cash flows in projects that have negative net present value. Then problem in gaining needed free cash flows can make them incapable of fulfilling the payment obligations on debt and the firm may encounter financial distress. This study investigates the effect of top executives’ overconfidence on financial distress. The target sample includes 103 firms listed in (TSE) during 2007 to 2011. In order to investigate the research hypotheses logistic regression model and independent samples t-test were applied. The evidence obtained in this study showed that companies managed by overconfident managers significantly indicate higher levels of financial distress. Results also showed that managerial overconfidence has a significant impact on financial distress.

This study investigate relation between political connections and auditor switching in the listed firms of Tehran Stock Exchange (TSE) during a 10-year period from 2003-2012. Using correlation method and binary logistic regression, the results of this study show that there is a positive relation between political connections and profitability with auditor switching. Evidence of the study also show that earnings management, audit fees, management change, leverage ratio, type of auditor report at the previous year and firm size don’t have a significant relation with auditor switching. So, research evidence claim that Iranian audit market has influenced by political issues.