Bankruptcy Probability: A Theoretical and Empirical Examination

Maurice Peat

in PhD Thesis from Finance Discipline Group, UTS Business School, University of Technology, Sydney

Abstract: Early Bankruptcy classification models were developed to demonstrate the usefulness of information contained in financial statements. 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 thesis seeks to provide an economic bl!sis for the selection of variables for inclusion in bankruptcy models, which are based on accounting information. An implicit assumption underlying this work is that the probability of default is endogenous. That is, the decisions of a firm's management have a direct impact on the probability of bankruptcy. These decisions and th~ir resultant effects can be identified through analysis of financial statements.

A model of a firm facing an uncertain environment with the possibility of bankruptcy is developed and analysed. In the model, a firm is created with given initial equity. These funds can be invested in productive resources or held as cash balances. The productive resources are used to earn random earnings in any period. If earnings are positive, they can be used to pay dividends to shareholders, invest in new productive resources, repay outstanding debt or increase the firm's cash balance. The firm is able to borrow and repay funds up to a credit limit. When the cash position of the firm falls to zero the firm is bankrupt. The firm attempts to maximise the stream of dividends paid to shareholders during its life. The solutions of the model and the associated bankruptcy probability expressions are derived by application of the dynamic programming algorithm.

Date: 2001
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