W.W. Grainger Beneish M-Score Historical Data
The historical data trend for W.W. Grainger'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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W.W. Grainger Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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|
|
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-2.56 |
-2.85 |
-2.26 |
-2.24 |
-2.58 |
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W.W. Grainger Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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|
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|
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-2.24 |
-2.26 |
-2.33 |
-2.38 |
-2.58 |
Competitive Comparison
For the Industrial Distribution subindustry, W.W. Grainger'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.
W.W. Grainger Beneish M-Score Distribution
For the Industrial Distribution industry and Industrials sector, W.W. Grainger's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where W.W. Grainger's Beneish M-Score falls into.
W.W. Grainger 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 W.W. Grainger 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 * 0.9497 | + | 0.528 * 0.9743 | + | 0.404 * 0.935 | + | 0.892 * 1.0821 | + | 0.115 * 1.0842 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9997 | + | 4.679 * -0.028231 | - | 0.327 * 0.9043 |
| = | -2.58 |
* 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 (Dec23) TTM: | Last Year (Dec22) TTM: |
Total Receivables was $2,192 Mil.
Revenue was 3997 + 4208 + 4182 + 4091 = $16,478 Mil.
Gross Profit was 1563 + 1655 + 1644 + 1634 = $6,496 Mil.
Total Current Assets was $5,274 Mil.
Total Assets was $8,147 Mil.
Property, Plant and Equipment(Net PPE) was $2,087 Mil.
Depreciation, Depletion and Amortization(DDA) was $214 Mil.
Selling, General, & Admin. Expense(SGA) was $3,931 Mil.
Total Current Liabilities was $1,831 Mil.
Long-Term Debt & Capital Lease Obligation was $2,647 Mil.
Net Income was 395 + 476 + 470 + 488 = $1,829 Mil.
Non Operating Income was 7 + 7 + 8 + 6 = $28 Mil.
Cash Flow from Operations was 604 + 523 + 450 + 454 = $2,031 Mil.
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Total Receivables was $2,133 Mil.
Revenue was 3802 + 3942 + 3837 + 3647 = $15,228 Mil.
Gross Profit was 1506 + 1519 + 1441 + 1383 = $5,849 Mil.
Total Current Assets was $4,977 Mil.
Total Assets was $7,588 Mil.
Property, Plant and Equipment(Net PPE) was $1,828 Mil.
Depreciation, Depletion and Amortization(DDA) was $205 Mil.
Selling, General, & Admin. Expense(SGA) was $3,634 Mil.
Total Current Liabilities was $2,010 Mil.
Long-Term Debt & Capital Lease Obligation was $2,602 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) |
| = | (2192 / 16478) | / | (2133 / 15228) |
| = | 0.133026 | / | 0.140071 |
| | = | 0.9497 |
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) |
| = | (5849 / 15228) | / | (6496 / 16478) |
| = | 0.384095 | / | 0.394223 |
| | = | 0.9743 |
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 - (5274 + 2087) / 8147) | / | (1 - (4977 + 1828) / 7588) |
| = | 0.096477 | / | 0.103189 |
| | = | 0.935 |
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 |
| = | 16478 | / | 15228 |
| | = | 1.0821 |
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)) |
| = | (205 / (205 + 1828)) | / | (214 / (214 + 2087)) |
| = | 0.100836 | / | 0.093003 |
| | = | 1.0842 |
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) |
| = | (3931 / 16478) | / | (3634 / 15228) |
| = | 0.238561 | / | 0.238639 |
| | = | 0.9997 |
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) |
| = | ((2647 + 1831) / 8147) | / | ((2602 + 2010) / 7588) |
| = | 0.54965 | / | 0.607802 |
| | = | 0.9043 |
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 |
| = | (1829 - 28 | - | 2031) | / | 8147 |
| | = | -0.028231 |
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.
W.W. Grainger has a M-score of -2.58 suggests that the company is unlikely to be a manipulator.
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