By Rick Finley-Oracle on Jan 15, 2015
As part of the new version of PSRM Analytics, we introduced the Altman Z Score and the Beneish Model M Score in the product. The following is an explanation of each calculation.
NYU Stern Finance Professor, Edward Altman, developed the Altman Z-score formula in 1967. In 2012, he released an updated version called the Altman Z-score Plus, that can be used to evaluate both public and private companies, both manufacturing and non-manufacturing companies and both U.S. and non-U.S. companies. Investors can use Altman Z-scores to help determine whether they should buy or sell a particular stock if they're concerned about the underlying company's financial strength. The Altman Z-score Plus can be used to evaluate corporate credit risk.
Definition of 'ALTMAN Z-SCORE'
The output of a credit-strength test that gauges a publicly traded manufacturing company's likelihood of bankruptcy. The Altman Z-score, is based on five financial ratios that can be calculated from data found on a company's annual 10K report. The Altman Z-score is calculated as follows:
Z-Score = 1.2A + 1.4B + 3.3C + 0.6D + 1.0E
A = Working Capital/Total Assets
B = Retained Earnings/Total Assets
C = Earnings Before Interest & Tax/Total Assets
D = Market Value of Equity/Total Liabilities
E = Sales/Total Assets
A score below 1.8 means the company is probably headed for bankruptcy, while companies with scores above 3.0 are not likely to go bankrupt. The lower/higher the score, the higher/lower the likelihood of bankruptcy.
Beneish Model - M Score
Created by Professor Messod Beneish, the M-Score is a mathematical model that uses eight financial ratios to identify whether a company has managed / manipulated its earnings. The variables are constructed from the company's financial statements and create a score to describe the degree to which the earnings have been manipulated. In many ways it is similar to the Altman Z-Score, but it is focused on detecting earnings manipulation rather than bankruptcy.
Interestingly, students from Cornell University using the M score correctly identified Enron as an earnings manipulator, while experienced financial analysts failed to do so.
Calculation / Definition of the M-Score
The M score is based on a combination of the following eight different indices:
- DSRI = Days’ Sales in Receivables Index. This measures the ratio of days’ sales in receivables versus prior year as an indicator of revenue inflation.
- GMI = Gross Margin Index. This is measured as the ratio of gross margin versus prior year. A firm with poorer prospects is more likely to manipulate earnings.
- AQI = Asset Quality Index. Asset quality is measured as the ratio of non-current assets other than plant, property and equipment to total assets, versus prior year.
- SGI = Sales Growth Index. This measures the ratio of sales versus prior year. While sales growth is not itself a measure of manipulation, the evidence suggests that growth companies are likely to find themselves under pressure to manipulate in order to keep up appearances.
- DEPI = Depreciation Index. This is measured as the ratio of the rate of depreciation versus prior year. A slower rate of depreciation may mean that the firm is revising useful asset life assumptions upwards, or adopting a new method that is income friendly.
- SGAI = Sales, General and Administrative expenses Index. This measures the ratio of SGA expenses to the prior year. This is used on the assumption that analysts would interpret a disproportionate increase in sales as a negative signal about firms future prospects
- LVGI = Leverage Index. This measures the ratio of total debt to total assets versus prior year. It is intended to capture debt covenants incentives for earnings manipulation.
- TATA - Total Accruals to Total Assets. This assesses the extent to which managers make discretionary accounting choices to alter earnings. Total accruals are calculated as the change in working capital accounts other than cash less depreciation.
The eight variables are then weighted together according to the following formula:
- M = -4.84 + 0.92*DSRI + 0.528*GMI + 0.404*AQI + 0.892*SGI + 0.115*DEPI – 0.172*SGAI + 4.679*TATA – 0.327*LVGI
There is also a five variable version which excludes SGAI, DEPI and LVGI (as these were not significant in the original Beneish model).
- M = -6.065 + 0.823*DSRI + 0.906*GMI + 0.593*AQI + 0.717*SGI + 0.107*DEP
The exact threshold varies depending on the probability of mis-classification but, broadly speaking, a score greater than -1.78 (i.e. less negative or positive number) indicates a strong likelihood of a firm being a manipulator.