پیوندهای مفید
آمار
| تعداد نشریات | 21 |
| تعداد شماره‌ها | 671 |
| تعداد مقالات | 9,774 |
| تعداد مشاهده مقاله | 69,543,943 |
| تعداد دریافت فایل اصل مقاله | 48,658,713 |
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 | ||
| تاریخ دریافت: 25 دی 1401، تاریخ بازنگری: 10 خرداد 1402، تاریخ پذیرش: 17 خرداد 1402 | ||
| 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 | ||
|
[1] M.N. Ashtiani and B. Raahmei, News-based intelligent prediction of financial markets using text mining and machine learning: A systematic literature review, Expert Syste. Appl. (2023), 119509. [2] H. Bang and D. Selva, Discovering generalized design knowledge using a multi-objective evolutionary algorithm with generalization operators, Expert Syste. Appl. 143 (2020), 113025. [3] M.H. Chen, W.G. Kim, and Ch.Y. Chen, An investigation of the mean reversion of hospitality stock prices towards their fundamental values: The case of Taiwan, Int. J. Hospital. Manag. 26 (2007), no. 2, 453–467. [4] J. Cunado and F. P. de Gracia, Oil price shocks and stock market returns: Evidence for some european countries, Energy Econ. 42 (2014), 365–377. [5] J.H.V.H. De Wet and E. Du Toit, Return on equity: A popular, but flawed measure of corporate financial performance, South Afr. J. Bus. Manag. 38 (2007), no. 1, 59–69. [6] P. Farshadi, Analyzing the performance of insurance companies and predicting future performance: a hybrid approach of fuzzy TOPSIS and artificial neural networks, Master’s thesis, Tarbiat Modares University, Tehran, Iran, 2017. [7] D. Furlaneto, L. Soares de Oliveira, D. Menotti, and G. Cavalcanti, Bias effect on predicting market trends with emd, Expert Syste. Appl. 82 (2017). [8] M.A. Goldberg, R.W. Helsley, and M.D. Levi, The location of international financial activity: An interregional analysis, Reg. Stud. 23 (1989), no. 1, 1–7. [9] J.H. Holland, Genetic algorithms and adaptation, Adapt. Control Ill-defined Syst. (1984), 317–333. [10] L. Huang and J. Wang, Forecasting energy fluctuation model by wavelet decomposition and stochastic recurrent wavelet neural network, Neurocomputing 309 (2018), 70–82. [11] Ch.E. Jordan, S.J. Clark, and W.R. Smith, Should earnings per share (eps) be taught as a means of comparing intercompany performance?, J. Educ. Bus. 82 (2007), no. 6, 343–348. [12] J. Kang, K. Kim, and W.C. Henderson, Economic value added (EVA): A financial performance measure, J. Account. Finance Res. 10 (2002), no. 1, 48. [13] S. Kumar and D.P. Warne, Parametric determinants of price-earnings ratio in Indian capital markets, IUP J. Appl. Finance 15 (2009), no. 9, 63. [14] L. Mohammadi-Karizek, Investigating the impact of new product strategy on company performance with the moderating role of CEO optimism (evidence from Tehran Stock Exchange), Master’s thesis, Khord Higher Education Institute, Bushehr-Iran, 2021. [15] M. Motallebi, M. Alizadeh, and S. Faraji-Dizaji, Estimating shadow economy and tax evasion by considering the variables of government financial discipline and behavioral factors in Iran’s economy, Iran. Econ. Rev. 24 (2020), no. 2, 515–544. [16] M. Pasha, Using the probabilistic approach to improve the prediction of financial performance of companies, Master’s thesis, Islamic Azad University, Chalous, Iran, 2022. [17] Y. Peng, P.H.M. Albuquerque, H. Kimura, and C.A.P.B. Saavedra, Feature selection and deep neural networks for stock price direction forecasting using technical analysis indicators, Machine Learn. Appl. 5 (2021), 100060. [18] S. Salimzadeh, Comparison of statistical algorithms and machine learning to predict the financial performance of companies, Master’s thesis, Urmia University, Urmia, Iran, 2022. [19] C.J. Simon and M.W. Sullivan, The measurement and determinants of brand equity: A financial approach, Market. Sci. 12 (1993), no. 1, 28–52. [20] M. Vogl, P. G. Rotzel, and S. Homes, Forecasting performance of wavelet neural networks and other neural network topologies: A comparative study based on financial market data sets, Machine Learn. Appl. 8 (2022), 100302. [21] X.SH. Yang, Cuckoo search and Firefly Algorithm: Theory and Applications, vol. 516, Springer, 2007. [22] Y. Yang and J. Wang, Forecasting wavelet neural hybrid network with financial ensemble empirical mode decomposition and mcid evaluation, Expert Syst. Appl. 166 (2021), 114097. [23] O.C. Yolcu and U. Yolcu, A novel intuitionistic fuzzy time series prediction model with cascaded structure for financial time series, Expert Syst. Appl. 215 (2023), 119336. | ||
|
آمار تعداد مشاهده مقاله: 1,131 تعداد دریافت فایل اصل مقاله: 758 |
||