Bankruptcy prediction is the art of predicting bankruptcy and various measures of financial distress of public firms. It is a vast area of finance and accounting research. The importance of the area is due in part to the relevance for creditors and investors in evaluating the likelihood that a firm may go bankrupt.
The quantity of research is also a function of the availability of data: for public firms which went bankrupt or did not, numerous accounting ratios that might indicate danger can be calculated, and numerous other potential explanatory variables are also available. Consequently, the area is well-suited for testing of increasingly sophisticated, data-intensive forecasting approaches.
The history of bankruptcy prediction includes application of numerous statistical tools which gradually became available, and involves deepening appreciation of various pitfalls in early analyses. Interestingly, research is still published that suffers pitfalls that have been understood for many years.
Bankruptcy prediction has been a subject of formal analysis since at least 1932, when FitzPatrick published a study of 20 pairs of firms, one failed and one surviving, matched by date, size and industry, in The Certified Public Accountant. He did not perform statistical analysis as is now common, but he thoughtfully interpreted the ratios and trends in the ratios. His interpretation was effectively a complex, multiple variable analysis.
In 1968, in the first formal multiple variable analysis, Edward I. Altman applied multiple discriminant analysis within a pair-matched sample. One of the most prominent early models of bankruptcy prediction is the Z-Score Financial Analysis Tool, which is still applied today.
|This section does not cite any references or sources. (February 2014)|
Survival methods are now applied.
Option valuation approaches involving stock price variability have been developed.
Neural network models and other sophisticated models have been tested on bankruptcy prediction.
Comparison of differing approaches
The latest research within the field of Bankruptcy and Insolvency Prediction compares various differing approaches, modelling techniques, and individual models to ascertain whether any one technique is superior to its counterparts.
Jackson and Wood (2013) provides an excellent discussion of the literature to date, including an empirical evaluation of 15 popular models from the existing literature. These models range from the univariate models of Beaver through the multidimensional models of Altman and Ohlson, and continuing to more recent techniques which include option valuation approaches. They find that models based on market data - such as an option valuation approach - outperform those earlier models which rely heavily on accounting numbers.
||This article includes a list of references, but its sources remain unclear because it has insufficient inline citations. (February 2014)|
- FitzPatrick 1932
- Beaver 1966. Financial ratios predictors of failure. Journal of Accounting Research, 4 (Supplement), p. 71-111.
- Beaver 1968
- Altman, Edward I. 1968. "Financial ratios, discriminant analysis and the prediction of corporate bankruptcy". Journal of Finance 23 (4), p. 589-609.
- Ohlson, James. 1980.
- Balcaen, Sofie and Hubert Ooghe. 2006. "35 years of studies on business failure: an overview of the classic statistical methodologies and their related problems," British Accounting Review 38, p 63-93.
- Zmijewski, Mark E. 1984. "Methodological issues related to the estimation of financial distress prediction models". Journal of Accounting Research 22 (Supplement), p. 59-86.
- Jackson, Richard and Wood, Anthony. (2013) The Performance of Insolvency Prediction and Credit Risk Models in the UK: A Comparative Study. The British Accounting Review, 45 (3) p. 183-202