Welcome to Open Science
Contact Us
Home Books Journals Submission Open Science Join Us News
Book-Based VS. Market-Based Indebtedness Ratios in Bankruptcy Prediction on the Polish Capital Market
Current Issue
Volume 4, 2017
Issue 5 (October)
Pages: 45-49   |   Vol. 4, No. 5, October 2017   |   Follow on         
Paper in PDF Downloads: 81   Since Oct. 25, 2017 Views: 530   Since Oct. 25, 2017
Jacek Welc, Department of Regional Economics, Wroclaw University of Economics, Wroclaw, Poland.
Forecasting corporate bankruptcy constitutes an integral and relevant part of financial statement analysis and business valuation. Typically the evaluation of a risk of financial default is based on some ratios, including company’s indebtedness. However, there are various versions of such metrics. In this paper, the book-based and market-based corporate indebtedness ratios are evaluated and compared in terms of the accuracy of their bankruptcy predictions, within a sample of data from the Polish market. The study is based on a sample of 80 firms, in which case at least one bankruptcy filing was announced in a period between the beginning of 2009 and the end of 2015. This sample is compared to the counter-sample of 80 randomly selected firms in which case no any bankruptcy filing occurred in the same years. The general usefulness of both versions of indebtedness ratio in credit risk evaluation has been confirmed by the statistical analysis presented in this study. Despite significant heterogeneity of the sample (which covers wide variety of businesses), the univariate logit models with only one ratio used as an explanatory variable are capable of identifying bankrupt firms (with one-period-ahead forecast horizon) in about 67-71% of cases. However, the research presented in this paper has not confirmed the supremacy of market-based indebtedness ratio over book-based one in predicting corporate financial distress.
Bankruptcy Prediction, Ratio Analysis, Fundamental Analysis, Indebtedness Ratio
W. H. Beaver, M. McNichols and J. W. Rhie, “Have Financial Statements Become Less Informative? Evidence From the Ability of Financial Ratios to Predict Bankruptcy”, Review of Accounting Studies, vol. 10, no. 1, pp. 93-122, 2005.
J. B. Caouette, E. I. Altman, P. Narayanan and R. W. J. Nimmo, Managing Credit Risk. The Great Challenge for Global Financial Markets. Hoboken: John Wiley & Sons, 2008.
C. Charalambous, A. Charitou, A. and F. Kaourou, “Comparative Analysis of Artificial Neural Network Models: Application in Bankruptcy Prediction”, Annals of Operations Research, vol. 99, pp. 403-425, 2000.
S. Chava and R. A. Jarrow, “Bankruptcy Prediction with Industry Effects”, Review of Finance, vol. 8, no. 4, pp. 537-569, 2004.
F. R. David, Strategic Management. Concepts and Cases. Upper Saddle River: Prentice Hall, 2011.
G. Giroux, Detecting Earnings Management. Hoboken: John Wiley & Sons, 2004.
J. E. Ketz, Hidden Financial Risk. Understanding Off-Balance Sheet Accounting. Hoboken: John Wiley & Sons, 2004.
T. Kraft, “Rating Agency Adjustments to GAAP Financial Statements and Their Effect on Ratings and Credit Spreads”, The Accounting Review, vol. 90, no. 2, pp. 641-674, 2015.
B. Mackenzie, D. Coetsee, T. Njikizana, R. Chamboko, B. Colywas and B. Hanekom, Interpretation and Application of International Financial Reporting Standards. Hoboken: John Wiley & Sons, 2012.
J. A. Ohlson, “Financial Ratios and the Probabilistic Prediction of Bankruptcy”, Journal of Accounting Research, vol. 18, pp. 109-131, 1980.
S. P. Pratt and A. V. Niculita, Valuing a Business. The Analysis and Appraisal of Closely Held Companies. New York: McGraw-Hill, 2008.
T. Shumway, “Forecasting Bankruptcy More Accurately: A Simple Hazard Model”, Journal of Business, vol. 74, no. 1, pp. 101-124, 2001.
C. P. Stickney, P. R. Brown and J. M. Wahlen, Financial Reporting and Statement Analysis. A Strategic Perspective. Mason: Thomson South-Western, 2004.
T. L. Wheelen and J. D. Hunger, Strategic Management and Business Policy. New York: Addison Wesley, 1995.
G. I. White, A. C. Sondhi and D. Fried, The Analysis and Use of Financial Statements. Hoboken: John Wiley & Sons, 2003.
C. White, Strategic Management. New York: Palgrave Macmillan, 2004.
M. E. Zmijewski, “Methodological Issues Related to the Estimation of Financial Distress Prediction Models”, Journal of Accounting Research, vol. 22, pp. 59-82, 1984.
Open Science Scholarly Journals
Open Science is a peer-reviewed platform, the journals of which cover a wide range of academic disciplines and serve the world's research and scholarly communities. Upon acceptance, Open Science Journals will be immediately and permanently free for everyone to read and download.
Office Address:
228 Park Ave., S#45956, New York, NY 10003
Phone: +(001)(347)535 0661
Copyright © 2013-, Open Science Publishers - All Rights Reserved