Designing a Bankruptcy Prediction Model Based on Account, Market and Macroeconomic Variables (Case Study: Cyprus Stock Exchange)

Document Type: Research Paper


1 Department of Management, Faculty of Humanities, University of Mohaghegh Ardabili, Ardabil, Iran

2 Faculty of Business Management, European University of Cyprus, Nicosia, Cyprus


The development of the Cyprus Stock Exchange together with the increasing trend of investors’ presence in financing activities has led to the importance of this market. In such circumstances, the first step towards a sustainable development of the Exchange is to support the investors. Risk of bankruptcy for the investee is a major challenge that an inexperienced stock investor encounters. In this study, for predicting bankruptcy, an attempt has been made to design a valid and accurate model that could act as a deterrent to improper stock selection. In most of the previous studies, non-native models have been used to predict bankruptcy in companies. However, the present study has attempted to overcome the shortcomings of the earlier studies through designing an indigenous model based on the data collected from 53 non-financial companies out of 103 listed companies in the Cyprus Stock Market from 2007 to 2012, using a complete set of variables affecting bankruptcy (accounting, market and macroeconomic variables), and with using the logistic regression method. The results showed that the accuracy of bankruptcy models that are based on accounting and market variables has been respectively 91.2% and 82.1%, respectively. On the other hand, it was shown that there is no significant relationship between macroeconomic variables and the probability likelihood of bankruptcy.


Main Subjects

Article Title [Persian]

طراحی مدل پیش‌بینی ورشکستگی با به‌کارگیری متغیرهای حسابداری، بازار و اقتصاد کلان (مطالعة موردی: بروس اوراق بهادار

Authors [Persian]

  • باقر عسگرنژاد نوری 1
  • میلاد سلطانی 2
1 گروه مدیریت، دانشکدة علوم انسانی، دانشگاه محقق اردبیلی، اردبیل، ایران
2 دانشکدة مدیریت بازرگانی، دانشگاه اروپایی قبرس، نیکوزیا، قبرس
Abstract [Persian]

هدف: توسعة بورس اوراق بهادار قبرس همراه با روند صعوی حضور سرمایه‌گذاران در فعالیت‌های مالی سبب شده است تا این بازار از اهمیت خاصی برخوردار شود. در چنین شرایطی، اولین گام جهت توسعة پایدار بورس اوراق بهادار قبرس حمایت از سرمایه‌گذاران است. ریسک ورشکستگی سرمایه‌گذاری یکی از چالش‌های اصلی است که سرمایه‌گذاران بی‌تجربه با آن مواجه‌اند. بر این اساس در این پژوهش تلاش شده است تا مدلی معتبر و دقیق برای پیش‌بینی ورشکستگی طراحی شود تا بدین طریق از انتخاب سهام نامناسب توسط سرمایه‌گذاران اجتناب شود. روش: در بسیاری از پژوهش‌های قبلی، مدل‌های غبربومی برای پیش‌بینی ورشکستگی شرکت‌ها استفاده شده است. با وجود این، در پژوهش حاضر قصد بر این است تا با طراحی مدلی بومی، ضعف‌های مدل‌های قبلی پوشش داده می‌شود. بدین منظور داده‌های پژوهش بر اساس انتخاب 53 شرکت غیرمالی از 103 شرکت پذیرفته‌شده در بورس اوراق بهادار قبرس طی دورة زمانی 2012-2007 گردآوری شد. مدل مورد نظر نیز با به‌کارگیری مجموعة کاملی از متغیرهای حسابداری، بازار و اقتصاد کلان و با استفاده از روش رگرسیون لجستیک تخمین زده شد. نتایج: دقت مدل‌های ورشکستگی مبتنی بر متغیرهای حسابدری و بازار به ترتیب برابر با 2/91 و 1/82 درصد است. از سوی دیگر، ارتباط معناداری بین متغیرهای اقتصاد کلان و احتمال ورشکستگی شرکت‌ها وجود نداشت.

Keywords [Persian]

  • پیش‌بینی ورشکستگی
  • متغیرهای اقتصاد کلان
  • متغیرهای بازار
  • متغیرهای حسابداری
  1. Agarwal, A. & Taffler, b., (2008). “Comparing the performance of market-based and accounting-based bankruptcy prediction models”. Journal of Banking & Finance, 32 (514), 1541-51.
  2. Aliakbari, S., (2009). “Prediction of corporate bankruptcy for the UK firms in manufacturing industry”. Department of Economics and Finance, School of Social Sciences, Brunel University.
  3. Altman, E.I., (1968). “Financial ratios, discriminant analysis and the prediction of corporate bankruptcy”. Journal of Finance. 23(4), 589-609.
  4. Aziz, M. & Dar, H.A., (2006). “Predicting corporate bankruptcy: where we stand? Corporate Governance”. Emerald Group Publishing Limited.,6(1), 18-33.
  5. Beaver, W., (1966). “Alternative accounting measures as predictors of failure”. The Accounting Review. 43(1), 113-122.
  6. Beaver, W.H., McNicjols, M.F. & Rhie, J.W., (2005). “Have financial statements become less informative? Evidence from the ability of financial ratios to predict bankruptcy”, Review of Accounting Studies, 10(1).
  7. Brédart, X., (2014). “Bankruptcy prediction model: The case of the United State”. International Journal of Economics and Finance, 6(3).
  8. Christidis, A. C. & Gregory, A., (2010). “Some new models for financial distress prediction in the UK”, Business School, University of Exeter.
  9. Cyprus Stock Exchange, (2008). “Annual report”. Available at:
  10. Dastgir, M., Sajadi, S. H. & Moghaddam, J. (2009). “Using logit model in corporate bankruptcy prediction”. Economic Journal, 8(4), 171-189.
  11. European Commission, (2014. “Guidelines on State aid for rescuing and restructuring non-financial undertakings indifficulty”, 20(a), 9. Available at:
  12. Fadaeinejad, M. E. & Eskandari, R., (2011). “Design and explanation of bankruptcy prediction models in Tehran Stock Exchange”, Accounting Research. 3(9), 38-55.
  13. Gang, X. J., Wang, J. & Ding Qiu, Z., (2004). “Effectiveness of Neural Network s for prediction of corporate financial distress in china”, Springer Berlin Heidelberg, 994-999.
  14. Gord, A., Habibi K. V., (2009). “Assessing financial capability of pharmaceutical companies using Springate model”. Economic Research and Policies, 52, 115-134.
  15. Gordon, M.J., (1971). “Towards a theory of financial distress”. The Journal of Finance, 26(2), 347-356.
  16. Hajiha, Z., (2005). “Collapse of the company, its causes and stages: A study of iranian and international bankruptcy law systems”. Auditor Quarterly, 29, 64-72.
  17. Hassani, M. & Parsadmehr, A., (2012). “The presentation of financial crisis forecast pattern (Evidence from Tehran Stock Exchange)”. International Journal of Finance and Accounting, 1 (6), 142-47.
  18. Hosmer, D., Lemeshow, S. & Sturdivant, R., (2013). “Applied logistic Regression”. Wiley Series in Probability and Statistics. Wiley.
  19. Karami, G. & Seyed Hosseni, M., (2012). “The usefulness of accounting information compared with market information in bankruptcy prediction”. Journal of Accounting Knowledge, 3(10), 93-116.           
  20. Laiki Bank Group. (2011). “Annual financial report”. Cyprus. Available at:
  21. Laitinen, T., &Kankaanpӓӓ, M., (1999). “Comparative analysis of failure prediction methods: the Finnish case”. The European Accounting Review, 8(1), 67-92.
  22. Newton, G. W., (2010). “Bankruptcy insolvency accounting practice and procedure”. 7th Edition. Wiley.
  23. Papadakis, G., (2008). “Bankruptcy prediction modeling in the Greek industrial sector”. Thesis, Athens Information Technology (Center of research and graduate education).
  24. Shirata, C.Y., (1998), “Financial ratios as predictors of bankruptcy in Japan: An empirical research”, Proceedings of the Second Asian Pacific Interdisciplinary Research in Accounting Conference, 437-445.
  25. Sulaiman , M., Ahmadu , A. & Sanda, M., (2001). “Predicting corporate failure in Malasia: An application of the logit model to financial ratio analysis”, Asian Academy of Management Journal, 6(1), 99-118.
  26. Tinoco, M. H. & Wilson, N., (2013), “Financial distress and bankruptcy prediction among listed companies using accounting, market and macroeconomic variables”, International Review of Financial Analysis, 30, 394-19.
  27. Vasantha, S., Vasantha, V. & Thiayalnayaki, D., (2013), “Prediction of business bankruptcy for selected Indian airline companies using Altman’s model”, International Journal of Research in Business Management, 1(4), 19-26.
  28. Veronica, M. & Anatadjaya, S.P., (2014). “Bankruptcy prediction model an industrial study in Indonesian publicly-listed firms during 1999-2010”. Integrative Business & Economics , 3, 18.
  29. Whitaker, R., (1999). “The early stage of financial distress”. Journal of Economics and Finance, 23(2), 123-133.