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Open Access Article
1 - Providing a model of earning transparency with emphasis on the criteria of the govermance system and performance: an artificial intelligence approach
fardin hafezi Mehrdad Ghanbari babak jamshidinavid Roohollah JamshidpourThe present study is aimed to present a model of earnings transparency with an artificial intelligence approach in companies listed on the Tehran Stock Exchange (TSE). For this purpose, the data of 167 companies during the years 2011 to 2018 were used to test the resear MoreThe present study is aimed to present a model of earnings transparency with an artificial intelligence approach in companies listed on the Tehran Stock Exchange (TSE). For this purpose, the data of 167 companies during the years 2011 to 2018 were used to test the research hypotheses. Variable selection test performed using Lasso's artificial intelligence algorithm showed that among the criteria of the audit committee's independence management system, the non-executive managers ratio, gender diversity and among the performance criteria, the ratio of cash holding in the company, operating profit margin and accounts receivable ratio had the highest effect to explain the earnings transparency of companies and also to predict the earnings transparency of the companies in the next year, the LARS algorithm method was used. The results of prediction showed the high power of Lars artificial intelligence algorithm to predict the earnings transparency of the companies listed on Tse. Keywords: Earnings Transparency, Corporate governance and performance criteria, Artificial Intelligence Approach Manuscript profile -
Open Access Article
2 - A mathematical model to predict corporate bankruptcy using financial, managerial and economic variables And compare it with other models
Jafar Zarin Babak Jamshidinavid Mehrdad Ghanbari Afshin BaghfalakiMany studies have been conducted in the field of bankruptcy prediction; But in most of them only financial ratios are used. However, in Iran, many non-financial factors affect bankruptcy. The main purpose of this study is to develop a mathematical model in which financi MoreMany studies have been conducted in the field of bankruptcy prediction; But in most of them only financial ratios are used. However, in Iran, many non-financial factors affect bankruptcy. The main purpose of this study is to develop a mathematical model in which financial and non-financial indicators such as management and economics factors are used to predict bankruptcy. In this study, 44 variables that had the greatest impact on bankruptcy forecast were selected and with confirmatory factor analysis, a questionnaire was developed and sent to experts in the fields of management, accounting and economics to rank the impact of these variables. The statistical sample of the study includes 200 bankrupt and non-bankrupt companies listed in the period 2009-2018. After collecting the questionnaires using the OLS regression estimation method, the variables that had a factor load of less than 0.5 were eliminated and in the final model 9 main variables. The research model identified 95% of bankrupt companies and 93% of non-bankrupt companies with 95.4% confidence. Then, for verification, two hypotheses were developed and the model of this research was compared with two existing models. The ability to distinguish bankrupt companies from non-bankrupt ones by our proposed model was 6% more accurate than the Pourheidari et al. model, and 9.4% more accurate than Altman’s model. Manuscript profile
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