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 assumpton 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 probabilty of 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.
Does the Beneish M-Score work?
Beneish used all the companies in the Compustat database between 1982-1992. In his out of sample tests, Beneish found that he could correctly identify 76% of manipulators, whilst only incorrectly identifying 17.5% of non-manipulators.
In a 2007 paper - The Predictable Cost of Earnings Manipulation - Beneish examines the use of the M score as a stock selection technique (over the period 1993-2003). The M-score strategy apparently generated a hedged return of nearly 14% per annum. A subsequent paper titled "Identifying Overvalued Equity" showed that an overvaluation score (O-Score) combining proxies for earnings overstatement, merger activity, stock issuance, and the manipulation of operating activities was able to identify firms with forecast abnormal price declines averaging -27%.
How can I run this Screen?
This is the link to the original paper on the Detection of Earnings Manipulation - as well as to a subsequent paper by Beneish - The Relation between Accruals and the Probability of Earnings Manipulation.
- Alex C Bell on the Beneish Indices
- Analysis ratios for detecting financial statement fraud
- James Montier: Earnings manipulation as source of short ideas
- Detecting Earnings Management - A Critical Assessment of the Beneish Model