The importance of quality on the application of the artificial intelligence algorithm in predicting profit smoothing

The smoothing of profit is a common category on the frontier of accounting and finance knowledge. One of the motivations for companies to smooth profits is to minimize the impact of taxes over time. In this study, using the information of 12 financial years in the Tehran Stock Exchange and using the financial information of 2019, the company has predicted the smoothing of profit with the communication machine vector algorithm. The results show that among the research variables, the variables of gross profit margin, earnings per share, sales returns, stock returns, conditional conservatism, ratio of operating cash to assets, stock price to earnings ratio and profit quality have a significant effect on current profit smoothing. Also, the linear and non-linear communication vector machine algorithm has the ability to predict the level of profit smoothing of companies listed on the Tehran Stock Exchange with high power. Another finding of the study is that the predictive algorithm of the communication vector machine has a higher ability than the linear algorithm of the communication vector to predict the smoothing of profit. No significant relationship was observed between the quality of the internal information environment and tax avoidance. The research findings show that when quality measurement accuracy management is used to measure the quality of the internal information environment, higher quality internal information environments face lower tax risks. Furthermore, when the criterion of non-renewal of financial statements was used, no significant relationship was observed between the quality of the internal information environment and tax risk.

کلیدواژه ها:

Application ، Artificial Intelligence ، Predicting ، Profit.