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
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
identified Enron as an earnings manipulator, while experienced financial
analysts failed to do so.
- See more at: http://www.stockopedia.com/content/the-beneish-m-score-identifying-earnings-management-and-short-candidates-56823/#sthash.ussLugk0.dpuf
Calculation / Definition of the M-Score
The M score is based on a combination of the following eight
- 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
- 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
- M = -4.84 + 0.92*DSRI +
0.528*GMI + 0.404*AQI + 0.892*SGI + 0.115*DEPI – 0.172*SGAI + 4.679*TATA –
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