Explanation of optimal financial performance forecasting model based on QTobins ratio by using data mining techniques | ||
| International Journal of Nonlinear Analysis and Applications | ||
| مقاله 3، دوره 15، شماره 9، آذر 2024، صفحه 23-39 اصل مقاله (624.79 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2023.30800.4498 | ||
| نویسندگان | ||
| Amir Hossein Moravveji؛ Farhad Dehdar* ؛ Ali Harimi | ||
| Department of Accounting, Shahrood Branch, Islamic Azad University, Shahrood, Iran | ||
| چکیده | ||
| The current research is based on the explanation of the optimal model for predicting the performance of companies using data mining techniques. The method of this research is of the applied type, in terms of the way of doing the work, it is of the descriptive-causal research type, and in terms of the time dimension, it is of the post-event research type. In the first step, by referring to databases such as theses, articles and similar researches, the required literature was collected in order to write the theoretical foundations and background of the research. In the following, the information of the investigated companies selected as a statistical sample, whose information is available in the form of data banks on CDs and is under the supervision and review of the responsible institutions, was audited by referring to the financial statements and New implementation software was compiled. The mentioned information included the financial data of the companies admitted to the Tehran Stock Exchange for a period of 10 years from the beginning of 2011 to the end of 2014. Finally, the findings showed that the firefly algorithm, genetic algorithm and evolutionary algorithm were effective in predicting the ratio of QTobins, return on equity and return on equity, and the firefly algorithm had a higher power to predict the ratio of QTobins, return on equity and return. has shares | ||
| کلیدواژهها | ||
| QTobins ratio؛ Caustic dada technique؛ Firefly algorithm؛ Magnetic algorithm؛ Integrative algorithm | ||
| مراجع | ||
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