Financial Performance Evaluation of Companies Using Decision Trees Algorithm and Multi-Criteria Decision-Making Techniques with an Emphasis on Investor’s Risk-Taking Behavior

Advances in Mathematical Finance and Applications

مقاله 9، دوره 6، شماره 3، مهر 2021، صفحه 555-566   

نوع مقاله: Research Paper

شناسه دیجیتال (DOI): 10.22034/amfa.2020.1897171.1405

نویسندگان

Zinat Ansari¹؛ Rezvan Hejazi^{* 2}؛ Yaghoob Zeraat kish³؛ Zabihallah Khani Masoum Abadi⁴

¹Department of accounting, Yasooj Branch, Islamic Azad University, Yasooj, Iran

²Scientific Member of Financial & AMP; Economic Faculty, Khatam University, Tehran, Iran

³Science and Research Branch, Islamic Azad university , Tehran, Iran

⁴Department of Accounting, Fasa Branch, Islamic Azad University, Fasa, Iran

چکیده

Evaluating the performance of companies using their financial ratios is a challenging task that is expected to become more straightforward by reducing the dimensionality of the data. The purpose of this study is to evaluate the performance of companies using a hybrid model for investment-related decision making through which the mean value of various financial ratios are calculated based on the investor's risk-taking behavior so that the number of all criteria is reduced to one single value for each alternative. To do so, a sample of 172 companies listed in Tehran Stock Ex-change was selected from 2008 to -2018. Firstly, the financial ratios were prioritized using decision trees regression analysis (type CART) and TOPSIS Technique. The results showed that Gross Profit Margin and Debt to Equity Ratio are the most and the least important factors, respectively. Then, using OWA (Ordered Weighted Averaging Aggregation) operator, the role of investor’s risk-taking behavior was investigated, and the results showed that investor’s risk-taking behavior changes the outcome of the decision-making process significantly.

کلیدواژه‌ها

Financial Ratios؛ TOPSIS Technique؛ OWA operator

مراجع

[1]               Bulgur, B. K., Application of TOPSIS Technique for Financial Performance Evaluation of Technology Firms in Istanbul Stock Exchange Market.  Procedia - Social and Behavioral Sciences, 2012, 62 (2012),p. 1033 – 1040.

[2]               Caro, N. P., Guardiola, M. and Ortiz, P., Classification trees as a tool to predict financial difficulties in Latin American companies through their accounting ratios. Contaduría y Administración, 2018, 63 (1), p. 25-26.

[3]               Cheng, C.H., Chen, C.T. and Huang, S.F., Combining fuzzy integral with order weight average (OWA) method for evaluating financial performance in the semiconductor industry. African Journal of Business Management,2012, 6(21),p. 6358-6368.

[4]               Delen, D., Kuzey, C., and Uyar, A., Measuring firm performance using financial ratios: A decision trees approach. Expert Systems with Applications,2013, 40, p. 3970–3983.

[5]               Izadikhah, M., Farzipoor Saen, R., Ranking sustainable suppliers by context-dependent data envelopment analysis. Ann Oper Res, 2020, 293, P.607–637, Doi: 10.1007/s10479-019-03370-4

[6]               Izadikhah, M., Khoshroo, A., Energy management in crop production using a novel fuzzy data envelopment analysis model, RAIRO-Oper. Res., 2018, 52 (2), P. 595-617, Doi: 10.1051/ro/2017082

[7]               Mahdavi, Gh. and Hosseini Azanakhari, M., What is the best criterion for the evaluation of financial performance? Economic Research Journal,2009, 4(31), p.121-146. https://www.sid.ir/fa/journal/ViewPaper.aspx?id=91729 [in Persian].

[8]               MacCrimmon, K.R., and Wehrung, D.A., Taking risks: The management of uncertainty, free press, New York,1986, https://trove.nla.gov.au/version/211445004.

[9]               MacCrimmon, K.R., and Wehrung, D.A., Characteristics of risk-taking executives. Management Science,1990,36(4), p. 422-435.

[10]            Omidi, M., Min, Q., Moradinaftchali, V., and Piri, M., The Efficacy of Predictive Methods in Financial Statement Fraud. Discrete Dynamics in Nature and Society2019, 2019(4), p. 1-12. Article ID 4989140, https://doi.org/10.1155/2019/4989140.

[11]            Pätäri, E., Karell, V., Luukka, P., and Yeomans, J. S., Comparison of the multicriteria decision-making methods for equity portfolio selection: The U.S. evidence. European Journal of Operational.Research, Elsevier, 2018,265(2), p. 655-672.

[12]             Ptak-Chmielewska, A., Predicting Micro-Enterprise Failures Using Data Mining Techniques. J. Risk and Financial Management. See discussions, stats, and author profiles for this publication,2019.   athttps://www.researchgate.net/publication/33104007

[13]            Parsa, B., Sarraf, F. Financial Statement Comparability and the Expected Crash Risk of Stock Prices. Advances in Mathematical Finance and Applications, 2018, 3(3), P. 77-93. Doi: 10.22034/amfa.2018.544951

[14]            Rizvi, A, and Ali, S.B., Risk-Taking Behavior of Investors of Pakistan, 2011 Online athttps://mpra.ub.uni-muenchen.de/64342/MPRA Paper No. 64342, posted 15 May 2015.

[15]            Salehi, A., Baharipour, A., Mohammadi, S. The Impact of Institutional Ownership on the Relationship between Tax and Capital Structure. Advances in Mathematical Finance and Applications, 2016, 1(2), P. 57-67. Doi: 10.22034/amfa.2016.527820

[16]            Shaout, A. and Yousif, M., Performance Evaluation – Methods and Techniques Survey, International Journal of Computer and Information Technology,2014, 3 (5), p. 966-979.

[17]            Staňková, M. and Hampel, D.,  Bankruptcy Prediction of Engineering Companies in the EU Using Classification Methods. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 2018, 66(5), p. 1347-1356.

[18]            Tone, K., Toloo, M., Izadikhah, M., A modified slacks-based measure of efficiency in data envelopment analysis, European Journal of Operational Research, 2020, 287 (2), P. 560-571, Doi: 10.1016/j.ejor.2020.04.019.

[19]            Wang, Y.J, and Lee, H.S., Evaluating the financial performance of Taiwan container shipping companies by strength and weakness indices. International Journal of Computer Mathematics,2010,87(1), p. 38-52.

[20]            Yager, R.R., New modes of OWA information fusion, International Journal of Intelligent Systems, 1998, 13 (7), p. 661-681.

[21]            Yalcin, N., Bayrakdaraglu, A., Kahraman, C., Application of fuzzy multi-criteria decision-making methods for financial performance evaluation of Turkish manufacturing industries, Expert Systems with Applications,2012,39(1), p. 350–364.

[22]            Yu. G and Wenjuan. G., Decision tree method in financial analysis of listed logistics companies, in 2010 international conference on intelligent computation technology and automation.

[23]            Zalaghi, H., Godini, M., mansouri, K. The Moderating Role of Firms characteristics on the Relationship between Working Capital Management and Financial Performance. Advances in Mathematical Finance and Applications, 2019, 4(1), P. 71-88. Doi: 10.22034/amfa.2019.581878.1158