Education for Practice
Calculating Solvency
Creating a Z-Score Calculator on Your PDA
Edward I. Altman’s z-score for predicting bankruptcy, introduced in 1968, was the precursor of credit-scoring models. Its application has since expanded to measure more than the publicly traded manufacturing companies investigated in Altman’s original paper. Using the following template—based on a paper by Arnold and Earl (2006)—you will be able to create a z-score calculator for your PDA. (In this case, we used an HP iPAQ PDA with Windows Mobile). While PDAs cannot take advantage of some of the Excel capabilities available on a PC, the Windows Mobile environment is functional enough to create a z-score template.
The z-score is based on a set of five ratios: X1 = (current assets - current liabilities) ÷ total assets; X2 = retained earnings ÷ total assets; X3 = EBIT (earnings before interest and taxes) ÷ total assets; X4 = (stock price × outstanding shares) ÷ total liabilities; and X5 = sales ÷ total assets. The z-score is defined as an equation with the five ratios: z = 1.2 × X1 + 1.4 × X2 + 3.3 × X3 + 0.6 × X4 + 0.999 × X5. A z-score below 1.81 indicates a high probability of failure, and a z-score above 2.99 indicates solvency. A z-score between 1.81 and 2.99 is inconclusive but generally not viewed as a positive sign.
The template requires nine readily available inputs: current assets, total assets, current liabilities, total liabilities, retained earnings, sales, EBIT, share price, and shares outstanding (see Figure 1). To finish the template, enter the coefficients into cells adjacent to the relevant ratio. The z-score is a matter of computing the above equation through cell references.
In the example below, the formulas entered into cells B13–B19 appear in red, and the results of the formulas appear in black. For these cells, only enter the red portion when replicating this template in Excel.
Figure 1: Z-Score Template
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Coefficients are designated in individual cells because nonmanufacturing and private firms use different coefficients for calculating the z-score than those shown in this example. However, if such flexibility within the template is not necessary, the template can be made more compact (see Figure 2).
Figure 2: Compact Z-Score Template
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The z-score is still a very popular measure of solvency, and given the computational ease of the z-score—which requires only readily available data—it is well worth referencing as an initial measure of solvency.
REFERENCES
Altman, Edward I., and Herbert A. Rijken. November 2004. “How Rating Agencies Achieve Rating Stability.” Journal of Banking and Finance, vol. 28, no. 11. 2679–2714.
Arnold, Tom, and John H. Earl, Jr. Summer 2006. “Applying Altman’s Z-Score in the Classroom.” Journal of Financial Education, vol. 32. 98–103.
Tom Arnold, PhD, CFA; John H. Earl Jr., PhD, CFA; and David S. North, PhD, are associate professors of finance at the Robins School of Business at the University of Richmond.
