Predicting Financial Failure Using the Logistics Regression Model: Evidence from Istanbul Stock Exchange / Lojistik Regresyon Modeli İle Finansal Başarısızlık Tahmini: Borsa İstanbul’da Bir Uygulama

Öz

In the globalizing world, the main objectives of companies are to make market value maximization and maintain their financial performance. Firms face financial failure if they cannot maintain their presence in the market in the face of increasing competition conditions and crises. In the study, it is aimed to make an estimation of financial failure by using the annual financial statements of the companies in the wholesale and retail sale trade sector (10 wholesale; 13 retail) operating in the Istanbul stock exchange for the period 2017-2021. According to the results of the Logistic Regression analysis, the successful prediction rate for 3 years varies between 86.7 % and 93.8 %. Considering the correct classification success of the models, it seems that logistic regression model estimations are a good tool for predicting the financial performance or failure of the business.

Anahtar Kelimeler

• Logistik regressiaon analysis
• Financial Failure Predicting
• Borsa Istanbul

Lojistik Regresyon Modeli İle Finansal Başarısızlık Tahmini: Borsa İstanbul’da Bir Uygulama / Predicting Financial Failure Using the Logistics Regression Model: Evidence from Istanbul Stock Exchange

Öz

Globalleşen dünyada, firmaların temel amaçları piyasa değeri maksimizasyonunu sağlamak ve finansal başarılarını devam ettirmektedir. Firmalar artan rekabet koşulları ve krizler karşısında piyasadaki varlıklarını devam ettiremedikleri takdirde finansal başarısızlık ile karşı karşıya kalmaktadırlar. Çalışmada, Borsa İstanbul A.Ş. (BIST)’de işlem gören toptan ve perakende ticaret sektöründeki şirketlerin (toptan 10; perakende 13) 2017-2021 dönemine ait yıllık finansal tabloları ve açıklamaları kullanılarak finansal başarısızlık tahmini yapılması amaçlanmıştır. Yapılan Lojistik Regresyon analizi sonuçlarına göre 3 yıl için başarılı tahmin oranı % 86.7 ile % 93.8 oranları arasında değişmektedir. Kullanılan modellerin doğru sınıflama başarılarını göz önüne alındığında, lojistik regresyon modeli tahminlerinin işletme finansal başarı ya da başarısızlığını önceden tahmininde iyi bir araç olduğu görülmektedir.

Anahtar Kelimeler

• Borsa İstanbul
• Lojistik Regresyon
• Finansal Başarısızlık tahmini

Kaynakça

1. Affes. Z. and Hentati-Kaffel, R. (2019). Predicting US Banks Bankruptcy: Logit Versus Canonical Discriminant Analysis. Computational Economics, 54(1), 199-244.
2. Aksoy. B. and Boztosun. D. (2018). Financial Failure Prediction Using Discriminant and Logistic Regression Methods: BIST Manufacturing Sector Example. Journal of Financial, Political and Economic Comments, 55, 9-32.
3. Aktaş, R. (1993). Endüstri İşletmeleri İçin Mali Başarısızlık Tahmini. Ankara: Türkiye İş Bankası Kültür Yayınları.
4. Alaka. H.A., Lukumon O. O., Hakeem A. O., Vikas K., Saheed O. A., Olugbenga O. A. and Muhammad B. (2018).
5. Systematic Review of Bankruptcy Prediction Models: Towards A Framework for Tool Selection. Expert Systems with Applications, 94, 164–84.
6. Altaş, D. and Giray, S. (2005). Mali Başarısızlığın Çok Değişkenli İstatistik Yöntemlerle Belirlenmesi: Tekstil Sektörü Örneği. Sosyal Bilimler Dergisi, 2, 13-28.
7. Altman, E. I. and Loris, B. (1976). A Financial Early Warning System for Over‐The‐Counter Broker‐Dealers. The Journal of Finance, 31(4), 1201-1217.
8. Altman, E.I. (1968). Financial Ratios. Discriminant Analysis and The Prediction of Corporate Bankruptcy. The Journal of Finance, 23, 589–609.

9. Altman. E. I., Iwanicz-Drozdowska. M., Laitinen. E. K. and Suvas. A. (2020). A Race for Long Horizon Bankruptcy Prediction. Applied Economics, 52(37), 4092-4111.
10. Baş. G. (2017). Türkiye'de Bir Şehrin Büyükşehir Olabilme Kriterlerinin İkili Lojistik Regresyon ile Analizi. (Yayınlanmamış Yüksek Lisans Tezi). Dumlupınar Üniversitesi, Sosyal Bilimler Enstitüsü, Kütahya.
11. Beaver, W. H. (1966). Financial Ratios as Predictors of Failure. Journal of Accounting Research, 4, 71-111.
12. Berkson, J. (1944). Application of the Logistic Function to Bio-Assay. Journal of the American Statistical Association, 39(227), 357-365.
13. Bulut, E. and Şimşek, A. İ. (2018). Financial Failure Estimation with Logistic Regression Model: A Study on Technology Sector Companies Treated in BIST. Anemon Muş Alparslan Üniversitesi Sosyal Bilimler Dergisi, 6(ICEESS’18), 177-183.
14. Casta, J-F. and Zerbib, J. P. (1979). Prévoir La Défaillance Des Entreprises?. Revue Française de Comptabilité, 97, 506–526.
15. Charalambakis, E. C. and Garrett, I. (2019). On Corporate Financial Distress Prediction: What Can We Learn from Private Firms in A Developing Economy? Evidence from Greece. Review of Quantitative Finance and Accounting, 52(2), 467-491.
16. Cornfıeld, J. (1962). Epidemiological Aspects of Coronary Artery Disease. Annals of The New York Academy of Sciences, 97, 959.
17. Cox, D. R. (1970). The Analysis of Binary Data. Methuen: London.
18. Cox, D.R. and Snell, E. (1989). Analysis of Binary Data. Chapman & Hall.
19. Deakin, E. B. (1972). A Discriminant Analysis of Predictors of Business Failure. Journal of Accounting Research, 10 (1), 167-179.
20. Du Jardin, P. (2009). Bankruptcy Prediction Models: How to Choose the Most Relevant Variables?. Bankers, Markets & Investors, 98, 39–46.
21. Ertan, A. S. and Ersan, Ö. (2018). Determinants of Financial Default: The Case of Manufacturing Industry in Turkey. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi, 40, 181-207.
22. Fitzpatrick, P.J. (1932). A Comparison of the Ratios of Successful Industrial Enterprises with Those of Failed Companies. Lanzhou: The Certified Public Account.
23. Gilbert, L. R., Menon, K. and Schwartz, K.B. (1990). Predicting Bankruptcy for Firms in Financial Distress. Journal of Business Finance & Accounting, 17(1), 161-171.
24. Gupta, J., Gregoriou, A. and Healy, J. (2015). Forecasting Bankruptcy For SMEs Using Hazard Function: To What Extent Does Size Matter?. Review of Quantitative Finance and Accounting, 45(4), 845-869.
25. Halperin, M., Blackwelder, W. C. and Verter, J. I. (1971). Estimation of The Multivariate Logistic Risk Function: A Comparison of the Discriminant Function and Maximum Likelihood Approaches. Journal of Clinical Epidemiology, 24, 125-158.
26. Jabeur, S. B. (2017). Bankruptcy Prediction Using Partial Least Squares Logistic Regression. Journal of Retailing and Consumer Services, 36, 197-202.
27. Kaygın, C. Y., Tazegül, A. ve Yazarkan, H. (2016). İşletmelerin Finansal Başarılı ve Başarısız Olma Durumlarının Veri Madenciliği ve Lojistik Regresyon Analizi İle Tahmin Edilebilirliği. Ege Academic Review, 16(1), 147-159.
28. Lev, B. (1971). Financial Failure and Informational Decomposition Measures, In Accounting in Perspective Contributions to Accounting Thoughts by Other Disciplines. Edited by R. R. Sterling and W. F. Bentz, Cincinnati: Southwestern Publishing Co.
29. Libby, R. (1975). Accounting Ratios and The Prediction of Failure: Some Behavioral Evidence. Journal of Accounting Research, 13(1), 150-161.
30. Nagelkerke, N. J. (1991). A Note On a General Definition of the Coefficient of Determination. Biometrika, 78(3), 691-692.
31. Ohlson, J. A. (1980). Financial Ratios and The Probabilistic Prediction of Bankruptcy. Journal of Accounting Research, 18(1), 109-131.
32. Önder, H. ve Cebeci, Z. (2002). Lojistik Regresyonlarda Değişken Seçimi. Çukurova Üniv. Ziraat Fakültesi Dergisi, 17(2), 105-114.
33. Shi, Y. and Li, X. (2019). An Overview of Bankruptcy Prediction Models for Corporate Firms: A Systematic Literature Review. Intangible Capital, 15(2), 114-127.
34. Stefko, R., Beata, G., Martin, R. and Viera, I. (2019). Evaluation of Selected Indicators of Patient Satisfaction and Economic Indices in OECD Country. Economics & Sociology, 12, 149–332.
35. Stenbäck, T. (2013). Corporate Default Prediction with Financial Ratios and Macroeconomic Variables. (Economics Master's Thesis). Department of Economics, Aalto University School of Business, Finland.
36. Tutkavul, K. ve Karahan, Ü. F. (2021). Lojistik Regresyon Analizi İle İşletmelerde Finansal Başarısızlığın Tahmin Edilmesi: BIST Sınai Endeksi'nde Bir Uygulama. Mali Çözüm Dergisi, 31(165), 45-60.
37. Ural, K., Gürard,. Ş. and Önemli, B. M. (2015). Financial Failure Estimation with Logistic Regression Model: Application in Food. Beverage and Tobacco Companies Listed on Borsa Istanbul. Journal of Accounting and Finance, 67, 85-100.
38. Zeytinoglu, E. and Akarım, Y. D. (2013). Financial Failure Prediction Using Financial Ratios: An Empirical Application On Istanbul Stock Exchange. Journal of Applied Finance & Banking, 3(3), 107-11.
39. Zohra, K. F., Mohamed, B., Elhamoud, T., Garaibeh, M., Ilhem, A. and Naimi, H. (2015). Using Financial Ratios to Predict Financial Distress of Jordanian Industrial Firm’s Empirical Study Using Logistic Regression. Academic Journal of Interdisciplinary Studies, 4(2), 137-137.