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BANKRUPTCY PREDICTION MODELS

Investors and creditors and their analysts employ accounting numbers in a variety of

ways, and one of the enduring practices is the prediction of corporate failure.

Bankruptcy is an important event to predict because of the dire consequences when it

occurs. Investors and creditors stand a chance to lose some or all of their investment

as well as forfeit chances for profits if a business enterprise collapses.A number of statistical models have been around for decades, and one of the most

popular prediction schemes is the Altman model.6 Edward Altman paired 33 failed

and 33 nonfailed firms in an attempt to control for industry and size differences. He

then employed a method called discriminant analysis to a list of 22 financial ratios.

This method builds the best linear model possible so that it can explain the firms as

failed or not failed with as little error as possible. The dependent variable in this

model denotes the bankruptcy status, in which a value of 1 denotes a company thathas not failed, while a value of 0 denotes that the entity has failed.

Altman started with a list of 22 financial ratios for the independent variables. Fromthis list he chose five that embrace the best possible model:

1. Working capital / total assets2. Retained earnings/ total assets3. Earnings before interest and taxes /total assets

4. Market value of equity/ book value of total debt5. Sales/ total assets

The coefficients for the model are shown in Exhibit 2.6. These coefficients of the

function were developed using the data from the first year prior to bankruptcy. The

same function was then used to predict corporate failure (regardless of the time

frame).

Testing the model on the original data and on a fresh set of data, Altman found that

themultiple discriminant analysis model seemed to be a reliable model up to two

years prior to bankruptcy.

The model can be used by entering the data into the model given in Exhibit 2.6.

Compute what is termed the Z-score by using the equation in the exhibit. Theninterpret the Z-score, depending on the resulting value. When the Z-score exceeds

2.99, predict that the business enterprise will not fail. If the Z-score is less than 1.81,then predict bankruptcy. If the value of the Z-score is between 1.81 and 2.99, then the

model is unable to categorize the firm as one that is likely to fail or not fail.

The key point to notice in yet another application is the importance of financial risk.One of the most important variables in the Altman model is market value of equity

divided by book value of total debts. This measure is merely a variation of the morecommon debt-to-equity measure of financial risk. The coefficient of this variable is

0.66, which of course is positive. This means that as there is more equity in the

financial structure, the less likely the business enterprise will collapse. Alternatively,

as debt is added to the financial structure, the lower this variable will be which in turn

lowers the Z-score and indicates that there is greater risk of corporate failure.

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Reference:

J. Edward Ketz,Hidden Financial Risk, Understanding OffBalance SheetAccounting, Published by John Wiley & Sons, Inc., Hoboken, New Jersey.