علیرضا مهرآذین

Purpose: Women studies have always been of interest to researchers. The issue of women's presence in business and management is one of the most important issues in the field of women's studies. This study sets to investigate the effect of characteristics of female managers who were either member of board or CEO on earning quality. Methodology: To this end, we collected necessary data such as financial statements from 102 Tehran Stock Exchange listed companies. The data belongs to period stretching from 20 Feb 2015 to 20 Feb 2020. To test our hypotheses, multivariate regression with panel data and also EViews software were utilized. The results show that the presence of female managers has a positive as well as meaningful effect on earning quality. Findings: Furthermore, the results of our second and third hypothesis indicate that the training skills of female managers and their experience in the board have a positive and significant relationship with the quality of companies’ earnings. Conclusion: According to the results of the research, it is recommended that women be used more in managerial positions and the existing misconceptions that have prevented skilled and experienced women from appearing should be discarded.

The purpose of this research is to investigate the reasons for tax evasion in companies, which uses two independent variables (financial constraints and tax planning opportunities) and tow dependent variable (firm value and tax evasion by tax difference method) in the form of 13 models. The 11 indicators have been considered for the variable of financial constraints of companies, and the model is implemented for all these indicators. The research was conducted in the 5-year period from 2015 to 2019 in the Tehran Stock Exchange, and Eviews software was used to analyse the data and fit them for 3 research hypotheses. The results of the research show that the opportunity for tax planning has a negative effect on the value of the company, and the increase in the opportunity for tax planning and subsequently tax evasion causes a decrease in the value of the company. Also, the research results showed that there is a significant relationship between tax planning opportunity and tax evasion (by tax differences method) of companies, while there is no positive relationship between financial constraints and tax evasion (by tax difference method) in companies that have tax planning opportunities.

So far, distress prediction models have been based on balanced, such sampling is not consistent with the reality of the statistical community of companies. If the data are balanced, the bias in sample selection may lead to an underestimation of typeI error and an overestimation of the typeII error of models. Although imbalanced data-based models are compatible with reality, they have a higher typeI error compared to balanced data-based models. The cost of typeI error is more important to Beneficiaries than the cost of typeII error. In this study, for reducing typeI error of imbalanced data-based models, random and clustering-based undersampling were used. Tested data included 760 companies since 2007-2007 with 4 different degrees and the results of the H1 to H3 test represented them. In all cases of the typeI error, typeII error of balanced data-based models were lower and more, respectively, compared to imbalanced data-based models; also, in most cases, the geometric mean of balanced data-based models was higher compared to imbalanced data-based models, respectively. The results of testing H4 to H6 show that in most cases, typeI error, typeII error and the geometric mean criterion of models based on modified imbalanced data were less, more, and more, respectiively compared to the models based on imbalanced data, in other words, applying Undersampling methods on imbalanced training data led to a decrease in typeI error and an increase in typeII error and geometric mean criteria. As a result using models based on modified imbalanced data is suggested to Beneficiaries

Financial statements should have general objectives rather than specific group interests. The possibility of forecasting earnings based on seasonal performance instead of the previous year's earnings and in terms of the contradiction between timeliness and the ability to verify earnings can be a new and thought-provoking issue. The present study examines stock price drift from the content of projected earnings forecast for quarterly operations. The research hypotheses were tested through univariate regression, multivariate regression and correlation coefficient tests using Eviews software. Findings of this study indicate that 1- Profit forecast based on quarterly performance has more verifiability than the previous year (profit stability). 2- The Verifiability of the year profit is more than the profit forecast based on the 9-month performance. 3- Stock price drift is expected on the day after the announcement of earnings and there are changes in earnings compared to the forecast of the previous season. 4- No relationship was observed between the volumes of shares traded the next day and the announcement of the forecasted profit and the changes in the profit compared to the forecast of the previous season.