Effects of Capital Market Cycle on Behavior of Prediction Patterns of Financial Distress

Document Type : Research Paper

Authors

1 Head of department in accounting

2 Associate Prof. in Accounting, Faculty of Economics and Management, Urmia University, Urmia, Iran

Abstract

This study aimed to investigate the effectiveness of capital market cycle on behavior of financial distress predicting patterns. In this study, the information of 211 distressed firms, selected by certain distress criteria, along with 211 healthy firms listed in the Tehran Stock Exchange in the period 2006-2015 have been used. The model estimation by the use of 35 selected indices in the two periods of capital market recession and expansion was carried out. In this study, Hodrich-Prescott Filter for determining capital market cycle and Logistic Regression and Support Vector Machine models for predicting financial distress were used.
The results showed that the behavior of financial distress predicting patterns are influenced by capital market cyclical variation in recession and expansion periods, but the influences are different in application of explaining variables and in predicting ability in the periods of recession and expansion. Also, the prediction ability in Support Vector Machine model is more than that in Logistic Regression model.

Keywords


بهرام فر، نقی؛ مهرانی، ساسان؛ غیور، فرزاد (1384). بررسی رابطۀ بین نسبت‌های نقدینگی سنتی و نسبت‌های حاصل از صورت جریان وجوه نقد جهت ارزیابی تداوم فعالیت شرکت‌ها، مجلۀ بررسی‌های حسابداری و حسابرسی، 12(40)، 18-3.
خلیفه سلطانی، سید احمد؛ اسماعیلی، فاطمه (1393). تأثیر چرخه تجاری بر پایداری مدل‌های پیش‌بینی ورشکستگی. پژوهش‌های تجربی حسابداری، 4(13)، 22-1.
محسنی، رضا؛ آقا بابایی، رضا؛ محمد قربانی، وحید (1392). پیش‌بینی درماندگی مالی با بکار بردن کارایی به‌عنوان یک متغیر پیش‌بینی کننده. فصلنامۀ پژوهش‌ها و سیاست‌های اقتصادی، 21(65)، 146-123.
مرادی، مهدی؛ فلاحی، محمدعلی؛ سلطانیان، زهره (1387). اثر چرخه‌های بازار سرمایه بر واکنش سرمایه‌گذاران نسبت به تغییرات غیرمنتظره اقلام تعهدی، مجله دانش و توسعه، 15(25)، 66-49.
منصور فر، غلامرضا؛ غیور، فرزاد؛ لطفی، بهناز (1394). توانایی ماشین بردار پشتیبان در پیش‌بینی درماندگی مالی. پژوهش‌های تجربی حسابداری، 5(1)، 195-177.
هادیان، ابراهیم؛ هاشم‌پور، محمدرضا (1382). شناسایی چرخه‌های تجاری در اقتصاد ایران. فصلنامه پژوهش‌های اقتصادی ایران، 5(15)، 120-93.
هومن، حیدر علی. (1390). تحلیل داده‌های چند متغیری در پژوهش رفتاری، تهران، پیک فرهنگ.
Asquith, P., Gertner, R., Scharfstein, D. (1994). Anatomy of financial distress: An examination of junk-bond issuers. Quarterly Journal of Economics, 109)3(, 1189-1222.
Bahramfar, N., Mehrani, S., Ghayour, F. (2005). The survey of relation between traditional liquidity ratios and cash flow statement ratios for going-concern evaluation. The Iranian Accounting and Auditing Review, 12(40), 3-18 [In Persian].
Chi, X., Lou, C., Yu, X. (2011). Financial distress prediction based on SVM and MDA methods: The case of Chinese listed companies. Quality and Quantity, 45(3), 671-686.
Claessens, S., Kose, M.A., Terrones, M.E. (2011). Gyrations in financial markets. Finance and Development, 48(1), 30-33.
Denis, D., Denis, D. (1995). Causes of financial distress following leveraged recapitalizations. Journal of Financial Economics, 37(2), 129-157.
Elloumi, F., Gueyié, J.P. (2001). Financial distress and corporate governance: An empirical analysis. Corporate Governance, 1(1), 15-23.
Gestel, T.V., Baesens, B., Suykens, J., Poel, D.V., Baestaens, D.E., Willekens, M. (2006). Bayesian kernel based classification for financial distress detection. European Journal of Operational Research, 172(3), 979-1003.
Gilbert, L.R., Menon, K., Schwartz, K.B. (1990). Predicting bankruptcy for firms in financial distress. Journal of Business Finance and Accounting, 17)1(, 161-171.
Gordon, M.J. (1971). Toward a theory of financial distress. The Journal of Finance, 26(2), 347-356.
Hadian, E., Hashempour, M. (2003). Business cycles in Iran. Quarterly Iranian Economic Research, 5(15), 93-120 [In Persian].
Hal, S. (2007). The influence of the business cycle on bankruptcy probability. International Transactions in Operational Research, 14(1), 75-90.
Hopwood, W., McKeown, J., Mutchler, J. (1994). A reexamination of auditor versus model accuracy within the context of the going-concern opinion decision. Contemporary Accounting Research, 10(2), 409-431.
Houman, H.A. (2011). Analysis of Multivariate Data in Behavioral Research. Tehran. Peyk-e-farhang [In Persian].
Khalifeh soltani, S.A., Esmaili, F. (2014). Business cycle and stability of bankruptcy prediction models. Journal of Empirical Research in Accounting, 4(13), 1–22 [In Persian].
Lau, A.H. (1987). A five-stage financial distress prediction model. Journal of Accounting Research, 25(1), 127-138.
Lizano, M.M., Garcia, D., Anton, M. (2011). The influence of the business cycle on the stability of business failure prediction models. European Accounting Association. 34th annual congress, 20-22 April 2011, Rome, Italy, 328-348.
Mansourfar, G., Ghayour, F., Lotfi, B. (2015). The ability of support vector machine (SVM) in financial distress prediction. Journal of Empirical Research in Accounting, 5(1), 177-195 [In Persian].
Moradi, M., Fallahi, M.A., Soltanian, Z. (2009). The effect of market cycles on investor’s reaction to discretionary accrual’s changes. Quarterly Knowledge and Development, 15(25), 49-66 [In Persian].
Mohseni, R., Agha babee, R., Ghorbani, V.M. (2013). Financial distress prediction with the use of the efficiency as a predictor variable. Quarterly Journal of Economic Research and Policies, 21(65), 123-146 [In Persian].
Opler, T., Titman, S. (1994). Financial distress and corporate performance. The Journal of Finance, 49(3), 1015-1040.
Shleifer, A., Vishny, R.W. (1997). A survey of corporate governance. Journal of Finance, 52(2), 737-783.
Ting, I., Lin, Y. (2011). What is missing? Using data mining techniques with business cycle phases for predicting company financial crises. Asia Pacific Management Review, 16(4), 535-549.
Ward, T.J., Foster, B.P. (1997). A note on selecting a response measure for financial distress. Journal of Business Finance and Accounting, 24(6), 869-879.