S&P Global Beneish M-Score Historical Data
The historical data trend for S&P Global's Beneish M-Score can be seen below:
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
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S&P Global Annual Data
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Trend |
Dec12 |
Dec13 |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
| Beneish M-Score |
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|
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-2.63 |
-2.37 |
-2.50 |
-2.89 |
-2.69 |
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S&P Global Quarterly Data
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Sep17 |
Dec17 |
Mar18 |
Jun18 |
Sep18 |
Dec18 |
Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
| Beneish M-Score |
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|
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-2.97 |
-2.91 |
-2.69 |
-1.53 |
-1.60 |
Competitive Comparison
For the Financial Data & Stock Exchanges subindustry, S&P Global's Beneish M-Score, along with its competitors' market caps and Beneish M-Score data, can be viewed below:
* Competitive companies are chosen from companies within the same industry, with headquarter located in same country, with closest market capitalization; x-axis shows the market cap, and y-axis shows the term value; the bigger the dot, the larger the market cap. Note that "N/A" values will not show up in the chart.
S&P Global Beneish M-Score Distribution
For the Capital Markets industry and Financial Services sector, S&P Global's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where S&P Global's Beneish M-Score falls into.
S&P Global Beneish M-Score Calculation
The M-score was created by Professor Messod Beneish. Instead of measuring the bankruptcy risk (Altman Z-Score) or business trend (Piotroski F-Score), M-score can be used to detect the risk of earnings manipulation. This is the original research paper on M-score.
The M-Score Variables:
The M-score of S&P Global for today is based on a combination of the following eight different indices:
| M | = | -4.84 | + | 0.92 * DSRI | + | 0.528 * GMI | + | 0.404 * AQI | + | 0.892 * SGI | + | 0.115 * DEPI |
| = | -4.84 | + | 0.92 * 1.226 | + | 0.528 * 1.0422 | + | 0.404 * 2.0713 | + | 0.892 * 1.2198 | + | 0.115 * 0.5924 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.3288 | + | 4.679 * -0.0139 | - | 0.327 * 0.4303 |
| = | -1.60 |
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
| This Year (Jun22) TTM: | Last Year (Jun21) TTM: |
Total Receivables was $2,125 Mil.
Revenue was 2993 + 2389 + 2088 + 2087 = $9,557 Mil.
Gross Profit was 1982 + 1640 + 1496 + 1544 = $6,662 Mil.
Total Current Assets was $6,235 Mil.
Total Assets was $64,323 Mil.
Property, Plant and Equipment(Net PPE) was $889 Mil.
Depreciation, Depletion and Amortization(DDA) was $524 Mil.
Selling, General, & Admin. Expense(SGA) was $2,702 Mil.
Total Current Liabilities was $4,958 Mil.
Long-Term Debt & Capital Lease Obligation was $11,408 Mil.
Net Income was 972 + 1235 + 675 + 797 = $3,679 Mil.
Non Operating Income was 566 + 1379 + 17 + 25 = $1,987 Mil.
Cash Flow from Operations was 454 + 222 + 940 + 967 = $2,583 Mil.
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Total Receivables was $1,421 Mil.
Revenue was 2106 + 2016 + 1867 + 1846 = $7,835 Mil.
Gross Profit was 1573 + 1489 + 1301 + 1329 = $5,692 Mil.
Total Current Assets was $6,932 Mil.
Total Assets was $13,398 Mil.
Property, Plant and Equipment(Net PPE) was $714 Mil.
Depreciation, Depletion and Amortization(DDA) was $201 Mil.
Selling, General, & Admin. Expense(SGA) was $1,667 Mil.
Total Current Liabilities was $3,315 Mil.
Long-Term Debt & Capital Lease Obligation was $4,608 Mil.
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1. DSRI = Days Sales in Receivables Index
Measured as the ratio of Revenue in Total Receivables in year t to year t-1.
A large increase in DSR could be indicative of revenue inflation.
| DSRI | = | (Receivables_t / Revenue_t) | / | (Receivables_t-1 / Revenue_t-1) |
| = | (2125 / 9557) | / | (1421 / 7835) |
| = | 0.22235011 | / | 0.18136567 |
| | = | 1.226 |
2. GMI = Gross Margin Index
Measured as the ratio of gross margin in year t-1 to gross margin in year t.
Gross margin has deteriorated when this index is above 1. A firm with poorer prospects is more likely to manipulate earnings.
| GMI | = | GrossMargin_t-1 | / | GrossMargin_t |
| = | (GrossProfit_t-1 / Revenue_t-1) | / | (GrossProfit_t / Revenue_t) |
| = | (5692 / 7835) | / | (6662 / 9557) |
| = | 0.72648373 | / | 0.69708067 |
| | = | 1.0422 |
3. AQI = Asset Quality Index
AQI is the ratio of asset quality in year t to year t-1.
Asset quality is measured as the ratio of non-current assets other than Property, Plant and Equipment to Total Assets.
| AQI | = | (1 - (CurrentAssets_t + PPE_t) / TotalAssets_t) | / | (1 - (CurrentAssets_t-1 + PPE_t-1) / TotalAssets_t-1) |
| = | (1 - (6235 + 889) / 64323) | / | (1 - (6932 + 714) / 13398) |
| = | 0.88924646 | / | 0.42931781 |
| | = | 2.0713 |
4. SGI = Sales Growth Index
Ratio of Revenue in year t to sales in year t-1.
Sales growth is not itself a measure of manipulation. However, growth companies are likely to find themselves under pressure to manipulate in order to keep up appearances.
| SGI | = | Sales_t | / | Sales_t-1 |
| = | Revenue_t | / | Revenue_t-1 |
| = | 9557 | / | 7835 |
| | = | 1.2198 |
5. DEPI = Depreciation Index
Measured as the ratio of the rate of Depreciation, Depletion and Amortization in year t-1 to the corresponding rate in year t.
DEPI greater than 1 indicates that assets are being depreciated at a slower rate. This suggests that the firm might be revising useful asset life assumptions upwards, or adopting a new method that is income friendly.
| DEPI | = | (Depreciation_t-1 / (Depreciaton_t-1 + PPE_t-1)) | / | (Depreciation_t / (Depreciaton_t + PPE_t)) |
| = | (201 / (201 + 714)) | / | (524 / (524 + 889)) |
| = | 0.21967213 | / | 0.37084218 |
| | = | 0.5924 |
Note: If the Depreciation, Depletion and Amortization data is not available, we assume that the depreciation rate is constant and set the Depreciation Index to 1.
6. SGAI = Sales, General and Administrative expenses Index
The ratio of Selling, General, & Admin. Expense(SGA) to Sales in year t relative to year t-1.
SGA expenses index > 1 means that the company is becoming less efficient in generate sales.
| SGAI | = | (SGA_t / Sales_t) | / | (SGA_t-1 /Sales_t-1) |
| = | (2702 / 9557) | / | (1667 / 7835) |
| = | 0.2827247 | / | 0.21276324 |
| | = | 1.3288 |
7. LVGI = Leverage Index
The ratio of total debt to Total Assets in year t relative to yeat t-1.
An LVGI > 1 indicates an increase in leverage
| LVGI | = | ((LTD_t + CurrentLiabilities_t) / TotalAssets_t) | / | ((LTD_t-1 + CurrentLiabilities_t-1) / TotalAssets_t-1) |
| = | ((11408 + 4958) / 64323) | / | ((4608 + 3315) / 13398) |
| = | 0.25443465 | / | 0.59135692 |
| | = | 0.4303 |
8. TATA = Total Accruals to Total Assets
Total accruals calculated as the change in working capital accounts other than cash less depreciation.
| TATA | = | (IncomefromContinuingOperations_t | - | CashFlowsfromOperations_t) | / | TotalAssets_t |
| = | (NetIncome_t - NonOperatingIncome_t | - | CashFlowsfromOperations_t) | / | TotalAssets_t |
| = | (3679 - 1987 | - | 2583) | / | 64323 |
| | = | -0.0139 |
An M-Score of equal or less than -1.78 suggests that the company is unlikely to be a manipulator. An M-Score of greater than -1.78 signals that the company is likely to be a manipulator.
S&P Global has a M-score of -1.60 signals that the company is likely to be a manipulator.
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