Anticipating Bankruptcy Reorganisation from Raw Financial Data Using Grammatical Evolution
This study using Grammatical Evolution, constructs a series of models for the prediction of bankruptcy, employing information drawn from financial statements. Unlike prior studies in this domain, the raw financial information is not preprocessed into pre-determined .nancial ratios. Instead, the ratios to be incorporated into the predictive rule are evolved from the raw financial data. This allows the creation and subsequent evolution of alternative ratio-based representations of the financial data. A sample of 178 publically quoted, US firms, drawn from the period 1991 to 2000 are used to train and test the model. The best evolved model in each time period correctly classified 78 (70)% of the firms in the out-of-sample validation set, one (three) year(s) prior to failure. The utility of a number of different Grammars for the problem domain is also examined.
KeywordsSales Revenue Grammatical Evolution Model Development Process Bankrupt Firm Compustat Database
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- 1.Altman, E. (1993). Corporate Financial Distress and Bankruptcy, New York: John Wiley and Sons Inc.Google Scholar
- 2.Morris, R. (1997). Early Warning Indicators of Corporate Failure: A critical review of previous research and further empirical evidence, London: Ashgate Publishing Limited.Google Scholar
- 3.Brabazon, T., O’Neill, M., Matthews, R., and Ryan, C. (2002). ‘Grammatical Evolution and Corporate Failure Prediction’, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2002), Spector et. al. Eds., New York, USA, July 9–13, 2002, pp. 1011–1019, Morgan Kaufmann.Google Scholar
- 4.Fitzpatrick, P. (1932). A Comparison of the Ratios of Successful Industrial Enterprises with Those of Failed Companies, Washington: The Accountants’ Publishing Company.Google Scholar
- 5.Smith, R. and Winakor, A. (1935). ‘Changes in the Financial Structure of Unsuccessful Corporations’, University of Illinois, Bureau of Business Research, Bulletin No. 51.Google Scholar
- 6.Beaver, W. (1968). ‘Financial Ratios as Predictors of Failure’, Journal of Accounting Research-Supplement: Empirical Research in Accounting, 71–102.Google Scholar
- 9.Zmijewski, M. (1984). ‘Methodological Issues Related to the Estimation of Financial Distress Prediction Models’, Journal of Accounting Research-Supplement, 59–82.Google Scholar
- 11.Shah, J. and Murtaza, M. (2000). ‘A Neural Network Based Clustering Procedure for Bankruptcy Prediction’, American Business Review, 18(2):80–86.Google Scholar
- 15.Altman, E. (2000). ‘Predicting Financial Distress of Companies: Revisiting the Zscore and Zeta models’, http://www.stern.nyu.edu/ ealtman/Zscores.pdf, October 2001.
- 16.Russel, P., Branch, B. and Torbey, V. (1999). ‘Market Valuation of Bankrupt Firms: is there an anomaly?’, Quarterly Journal of Business and Economics, 38:55–76.Google Scholar
- 17.Ferris, S., Jayaraman, N. and Makhija, A. (1996). ‘The Impact of Chapter 11 filings on the Risk and Return of Security Holders, 1979-1989’, Advances in Financial Economics, 2:93–118.Google Scholar
- 19.Ryan C., Collins J.J., O’Neill M. (1998). Grammatical Evolution: Evolving Programs for an Arbitrary Language. Lecture Notes in Computer Science 1391, Proceedings of the First European Workshop on Genetic Programming, 83–95, Springer-Verlag.Google Scholar
- 20.O’Neill M., Ryan C. (2001) Grammatical Evolution, IEEE Trans. Evolutionary Computation. 2001.Google Scholar
- 21.O’Neill, M. (2001). Automatic Programming in an Arbitrary Language: Evolving Programs in Grammatical Evolution. PhD thesis, University of Limerick, 2001.Google Scholar
- 22.Koza, J. (1992). Genetic Programming. MIT Press.Google Scholar
- 23.Hair, J., Anderson, R., Tatham, R. and Black, W. (1998). Multivariate Data Analysis, Upper Saddle River, New Jersey: Prentice Hall.Google Scholar
- 24.Argenti, J. (1976). Corporate Collapse: The Causes and Symptoms, London: McGraw-Hill.Google Scholar
- 25.Smith, T. (1992). Accounting for Growth. London: Century Business.Google Scholar