درخت حوزه‌های تخصصی

In this research, we have tried to investigate the effect of successive news of dis-tributed profits, negative adjustment and late announcement of an adjustment on the market reaction process in Iran. Following the design of the market response evaluation indicators, the transaction information was collected from the Stock Exchange in the five-year period of 2011-2015. The statistical sample consists of 125 companies selected by systematic elimination method and a total of 625 years-firms. To investigate the research hypotheses, linear regression and correlation have been used and for analyzing the data and testing the hypotheses, Eviews software has been used. What is summarized in the overall conclusion of the test of research hypotheses is that the successive news of distributed profits has an effect on the market reaction process;moreover, negative adjustment has a negative impact in the forecast of earnings per share and late announcement of the adjustment of the earnings per share on the market reaction process.Finally, the results indicated that the market's negative reaction to the late negative adjustment of the earnings per share forecasting is not lower than timely negative adjustment of earnings per share forecasting, and the positive reaction of the market to adjust the timely positive or zero forecast of earning per share, compared to adjusting the late positive or zero forecast of earnings per share is also no greater. the results obtained in this study are partly consistent with the documentation referenced in the theoretical framework of the research and financial literature

The accounting software is considered to be of the most critical components of accounting information system, with particular significance as of accounting and financial systems. the most important problems with accounting education systems is that students do not adequately learn the financial software required by the accounting profession, which, in turn, reduces the credibility and position of the accounting profession. That the main objective of accounting software education is to educate skilled and expert accountants to enter the accounting profession, which is considered as of the success factors of country’s economy. In this study, employ data mining techniques to investigate the accuracy, precision, and recall performance measures and to predict the rate of financial software learning based on accounting students’ emotional intelligence (EI), gender and education level. Accordingly, a machine-learning-based multivariate statistical analysis is performed on 100 Iranian accounting students. The results show that emotional intelligence has the most impact on the rate of financial software learning among the variables. Gender and education level were influential. Also, among the five algorithms, the highest precision and recall are achieved by both Decision Tree and XGBoost and are presented as the most appropriate models for the prediction rate of financial software learning.