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Abbaskhani, Hamid, Pakmaram, Asgar, Rezaei, Nader, Bahri Sales, Jamal. (1401). Predicting Going Concern of Companies Using the Tone of Auditor Reporting. سامانه مدیریت نشریات علمی, 2(2), 181-194. doi: 10.22054/jmmf.2023.15192
Hamid Abbaskhani; Asgar Pakmaram; Nader Rezaei; Jamal Bahri Sales. "Predicting Going Concern of Companies Using the Tone of Auditor Reporting". سامانه مدیریت نشریات علمی, 2, 2, 1401, 181-194. doi: 10.22054/jmmf.2023.15192
Abbaskhani, Hamid, Pakmaram, Asgar, Rezaei, Nader, Bahri Sales, Jamal. (1401). 'Predicting Going Concern of Companies Using the Tone of Auditor Reporting', سامانه مدیریت نشریات علمی, 2(2), pp. 181-194. doi: 10.22054/jmmf.2023.15192
Abbaskhani, Hamid, Pakmaram, Asgar, Rezaei, Nader, Bahri Sales, Jamal. Predicting Going Concern of Companies Using the Tone of Auditor Reporting. سامانه مدیریت نشریات علمی, 1401; 2(2): 181-194. doi: 10.22054/jmmf.2023.15192

Predicting Going Concern of Companies Using the Tone of Auditor Reporting

Journal of Mathematics and Modeling in Finance
دوره 2، شماره 2، فروردین 2023، صفحه 181-194  XML اصل مقاله (211.96 K)
نوع مقاله: Research Article
شناسه دیجیتال (DOI): 10.22054/jmmf.2023.15192
نویسندگان
Hamid Abbaskhaniorcid 1؛ Asgar Pakmaram email orcid 2؛ Nader Rezaeiorcid 2؛ Jamal Bahri Salesorcid 3
1Department of accounting
2Department of Accounting, Bonab Branch, Islamic Azad University, Bonab, Iran
3Department of Accounting, Urmia Branch, Islamic Azad University, Urmia, Iran
چکیده
Despite the growing need for research on the going concern and bankruptcy of companies, most of the conducted studies have used the approach of quantitative data for predicting the going concern and bankruptcy of companies; on the other hand, it is possible to manage these quantitative data by company managers. As a result, there appears to be a need to examine alternative methods for predicting going concern and bankruptcy based on qualitative data from the auditor's report. The purpose of this research is to determine the ability to predict the going concern of the companies using quantitative and qualitative data. The study period was from 2011 to 2021, with a sample of 54 companies admitted to the Tehran Stock Exchange. The results of the first hypothesis test show that the coefficient of determination of text-mining approach model prediction with the presence of a life cycle variable is greater than the determination coefficient of text-mining approach model prediction with the presence of a company size variable. The test of the second hypothesis shows that the difference in the increasing explanatory power of the first model compared to the second model in the companies accepted in the stock exchange is significant.
کلیدواژه‌ها
Financial Forecasting؛ Going Concern؛ Tone Analysis؛ Auditor Reporting
آمار
تعداد مشاهده مقاله: 61
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