Factors Affecting the Probability of Bankruptcy
|Date of publication:||September 2003|
|Working paper number:||130|
The majority of classification models developed have used a pool of financial ratios combined with statistical variable selection techniques to maximise the accuracy of the classifier being employed. Rather than follow an "ad hoc" variable selection process, this paper seeks to provide an economic basis for the selection of variables for inclusion in bankruptcy models, which are based on accounting information. Variables which occur in bankruptcy probability expressions derived from the solution of an stochastic optimising model for a firm are 'proxied' by variables constructed from financial statement data. The random nature of the life time of a single firm provides the rationale for the use of duration or hazard-based statistical methods in the validation of the derived bankruptcy probability expressions. The Cox (1972) proportional hazards model is used to estimate the coefficients and standard errors that are required for the validation of the derived bankruptcy probability expressions. Results of the validation exercise confirm that the variables included in the empirical hazard formulation behave in a way that is consistent with the model of the firm.
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|Comments:||Published as: Peat, M., 2007, "Factors Affecting the Probability of Bankruptcy: A Managerial Decision Based Approach", Abacus, 43(3), 303-324.|
Alfaro-Cid, E., Castillo, P. A., Esparcia, A., Sharman, K., Merelo, J. J., Prieto, A., Mora, A. M. and Laredo, J. L. J.,2008 , "Comparing Multiobjective Evolutionary Ensembles for Minimizing Type I and II Errors for Bankruptcy Prediction", IEEE World Congress on Computational Intelligence, Hong Kong, 1-6 June.
Bhaumik, S., Das, P. K. and Kumbhakar, S. C., 2011, "Firm Investment and Credit Constraints in India, 1997 – 2006: A Stochastic Frontier Approach", Working Paper Number: 1010, William Davidson Institute, University of Michigan.
Bhimani, A., Gulamhussen, M. A. and Lopes, S. D., 2010, "Accounting and Non-Accounting Determinants of Default: An Analysis of Privately-Held Firms", Journal of Accounting and Public Policy, 29(6), 517-532.
Chancharat, N., 2008, "An Empirical Analysis of Financially Distressed Australian Companies: The Application of Survival Analysis", PhD Thesis, University of Wollongong.
Fathi, S., Shahin, A., Shahrestani, A. and Sefanoor, M., 2012, "Meta Analysis of the Impact of Factors Related to Research Structure on the Strength of Bankruptcy Prediction Models and Variables", Journal of Basic and Applied Scientific Research, 2(10), 10095-10102.
Gama, A. P. M. and Geraldes, H. S. A., 2012, "Credit Risk Assessment and the Impact of the New Basel Capital Accord on Small and Medium-Sized Enterprises: An Empirical Analysis", Management Research Review, 35(8), 727-749.
López-Iturriaga, F. J., López-de-Foronda, Ó. and Sanz, I. P., 2010, "Predicting Bankruptcy Using Neural Networks in the Current Financial Crisis: A Study of U.S. Commercial Banks", Working Paper Number: 568, University De La Rioja.
Martin, S. and Peat, M., 2009, "A Comparison of the Information Content of Accounting and Market Measures in Distress", Working Paper.
Perederiy, V., 2009, "Bankruptcy Prediction Revisited: Non-Traditional Ratios and Lasso Selection", Working Paper.
Perederiy, V., 2010, "Insolvenzprognose für ukrainische, deutsche sowie nordamerikanische Unternehmen", Doctoral Thesis, Europa-Universität Viadrina
Routledge, J. and Morrison, 2012, "Insolvency Administration as a Strategic Response to Financial Distress", Australian Journal of Management, 37(3), 441-459.