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کاربرد نوع شرط:
- جایگاه : پژوهشی
- مجله: Iranian Journal of Finance
- نوع مقاله: Journal Article
- کلمات کلیدی: inflation,Earnings Management,political connections,Economic Indicators
- چکیده:
- چکیده انگلیسی: Governments always affect the economic environment as legislators in the field of business. The economic conditions governing the market and business require different conditions and contexts for decision making and corporate execution practices. Companies and managers administering them under environmental conditions, achieve their goals by employing various earnings management methods. Hence, the present study examines the effect of governments’ economic performance on the earnings management methods used in listed companies of Tehran Stock Exchange (2004-2016) for a sample of 16 industries and 271 companies. To test the hypotheses, multivariate regression model was used. The results showed that during the research period, companies managed earnings, and while more than 70% of companies used the accrual earnings management method, there was a relationship between annual economic indicators and real earnings management, and the change in general level of prices and the political connections of states have affected the relationship. Also, the accruals-based earnings management method occurred independent of annual economic indicators and there is a significant relationship between governments changes and earnings management methods.
- انتشار مقاله: 11-10-1348
- نویسندگان: Alireza Ghonji Feshki,Mohammad Hamed Khanmohammadi,Shohreh Yazdani
- مشاهده
- جایگاه : پژوهشی
- مجله: Advances in Mathematical Finance and Application
- نوع مقاله: Journal Article
- کلمات کلیدی: Data mining,Genetic Algorithm,financial reporting fraud,fraud detection
- چکیده:
- چکیده انگلیسی: both academic and auditing firms have been searching for ways to detect corporate fraud. The main objective of this study was to present a model to detect financial reporting fraud by companies listed on Tehran Stock Exchange (TSE) using genetic algorithm. For this purpose, consistent with theoretical foundations, 21 variables were selected to predict fraud in financial reporting that finally, using statistical tests, 9 variables including SALE/EMP, RECT/SALE, LT/CEQ, INVT/SALE, SALE/TA, NI/CEQ, NI/SALE, LT/XINT, and AT/LT were selected as the potential financial reporting fraud indexes. Then, using genetic algorithm, the final model of fraud detection in financial reporting was presented. The statistical population of this study included 66 companies including 33 fraudulent and 33 non-fraudulent companies from 2011 to 2016. The results showed that the presented model with the accuracy of 91.5% can detect fraudulent companies. These findings extend financial statement fraud research and can be used by practitioners and regulators to improve fraud risk models.
- انتشار مقاله: 11-04-1398
- نویسندگان: Mahmood Mohammadi,Shohreh Yazdani,Mohammadhamed Khanmohammadi
- مشاهده