Earlier this month, we discussed the Altman Z-Score and the Piotroski F-Score, which are measures of predicting the financial strength of firms. Today, we will discuss Beneish’s M-Score, which looks to determine whether a company has manipulated its earnings. The M-Score has been shown to correctly identify 76% of manipulators on an out of sample basis.
Here is the original M-Score formula:
M-Score = -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
Where,
In this original model, Beneish found that firms that scored greater than -2.22 were more likely to be earnings manipulators.
Here’s how Beneish summed up:
Additionally, you can read a later paper by Beneish that shows the accuracy of the M-Score, Identifying Overvalued Equity, here [PDF]. One interesting point to note is that Cornell University students used the M-Score to identify Enron as an earnings manipulator back in 1998, before the firm’s shenanigans were exposed.
So how should you use this? Like the Altman Z-Score and the Piotroski F-Score, I recommend incorporating the M-Score into your investment analysis spreadsheet and calculating the M-Score for any firm you are analyzing. Given how easy it is to calculate and its accuracy in predicting earnings manipulation, there really is no excuse for not considering it.
How do you incorporate the Beneish M-Score into your analysis?
Author Disclosure: None
Here is the original M-Score formula:
M-Score = -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
Where,
| Factor | Name | Formula | Basis |
| DSRI | Days’ Sales in Receivables Index | Receivables / Total Sales | This Year / Last Year |
| GMI | Gross Margin Index | Gross Profit / Total Sales | Last Year / This Year |
| AQI | Asset Quality Index | (Non-Current Assets – PP&E) / Total Assets | This Year / Last Year |
| SGI | Sales Growth Index | Total Sales | This Year / Last Year |
| DEPI | Depreciation Index | Depreciation / (Depreciation + Net PP&E) | Last Year / This Year |
| SGAI | SG&A Expense Index | SG&A / Revenues | This Year / Last Year |
| TATA | Total Accruals to Total Assets | Δ(Working Capital – Cash) – Depreciation | This Year / Last Year |
| LVGI | Leverage Index | Total Debt / Total Assets | This Year / Last Year |
Here’s how Beneish summed up:
This model consists of eight ratios that capture either financial statement distortions that can result from earnings manipulation (DSR, AQI, DEPI and Accruals) or indicate a predisposition to engage in earnings manipulation (GMI, SGI, SGAI, LEVI). The predictive ratios focusing on financial statement distortions capture unusual accumulations in receivables (DSR, indicative of revenue inflation), unusual expense capitalization and declines in depreciation (AQI and DEPI, both indicative of expense deflation), and the extent to which reported accounting profits are supported by cash profits (Accruals).You can read Beneish’s paper from 1999, The Detection of Earnings Manipulation, here [PDF].
Additionally, you can read a later paper by Beneish that shows the accuracy of the M-Score, Identifying Overvalued Equity, here [PDF]. One interesting point to note is that Cornell University students used the M-Score to identify Enron as an earnings manipulator back in 1998, before the firm’s shenanigans were exposed.
So how should you use this? Like the Altman Z-Score and the Piotroski F-Score, I recommend incorporating the M-Score into your investment analysis spreadsheet and calculating the M-Score for any firm you are analyzing. Given how easy it is to calculate and its accuracy in predicting earnings manipulation, there really is no excuse for not considering it.
How do you incorporate the Beneish M-Score into your analysis?
Author Disclosure: None
