Greif Beneish M-Score Historical Data
The historical data trend for Greif'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.
Greif Beneish M-Score Chart
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Greif Annual Data
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Trend |
Oct15 |
Oct16 |
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Oct18 |
Oct19 |
Oct20 |
Oct21 |
Oct22 |
Oct23 |
Oct24 |
| Beneish M-Score |
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-2.76 |
-2.16 |
-2.69 |
-2.82 |
-2.41 |
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Greif Quarterly Data
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Jul20 |
Oct20 |
Jan21 |
Apr21 |
Jul21 |
Oct21 |
Jan22 |
Apr22 |
Jul22 |
Oct22 |
Jan23 |
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Jan24 |
Apr24 |
Jul24 |
Oct24 |
Jan25 |
Apr25 |
| Beneish M-Score |
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-2.52 |
-2.40 |
-2.41 |
-2.47 |
-2.57 |
Competitive Comparison of Greif's Beneish M-Score
For the Packaging & Containers subindustry, Greif'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.
Greif's Beneish M-Score Distribution in the Packaging & Containers Industry
For the Packaging & Containers industry and Consumer Cyclical sector, Greif's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Greif's Beneish M-Score falls into.
Greif 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 Greif 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 * 0.9831 | + | 0.528 * 0.9944 | + | 0.404 * 0.9786 | + | 0.892 * 1.0589 | + | 0.115 * 0.8781 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0674 | + | 4.679 * -0.022015 | - | 0.327 * 0.9598 |
| = | -2.57 |
* 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 (Apr25) TTM: | Last Year (Apr24) TTM: |
Total Receivables was $804 Mil.
Revenue was 1385.7 + 1265.8 + 1417.1 + 1454.2 = $5,523 Mil.
Gross Profit was 319.5 + 245.5 + 288.7 + 290.4 = $1,144 Mil.
Total Current Assets was $1,754 Mil.
Total Assets was $6,754 Mil.
Property, Plant and Equipment(Net PPE) was $1,694 Mil.
Depreciation, Depletion and Amortization(DDA) was $268 Mil.
Selling, General, & Admin. Expense(SGA) was $662 Mil.
Total Current Liabilities was $1,386 Mil.
Long-Term Debt & Capital Lease Obligation was $2,529 Mil.
Net Income was 47.3 + 8.6 + 70.1 + 87.1 = $213 Mil.
Non Operating Income was -28.1 + -18.3 + -5.2 + 43.8 = $-8 Mil.
Cash Flow from Operations was 136.4 + -30.8 + 187.2 + 76.8 = $370 Mil.
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Total Receivables was $772 Mil.
Revenue was 1371 + 1205.8 + 1308.4 + 1330.3 = $5,216 Mil.
Gross Profit was 270.1 + 221.6 + 275.7 + 307 = $1,074 Mil.
Total Current Assets was $1,614 Mil.
Total Assets was $6,829 Mil.
Property, Plant and Equipment(Net PPE) was $1,799 Mil.
Depreciation, Depletion and Amortization(DDA) was $245 Mil.
Selling, General, & Admin. Expense(SGA) was $586 Mil.
Total Current Liabilities was $1,026 Mil.
Long-Term Debt & Capital Lease Obligation was $3,098 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) |
| = | (803.7 / 5522.8) | / | (772 / 5215.5) |
| = | 0.145524 | / | 0.14802 |
| | = | 0.9831 |
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) |
| = | (1074.4 / 5215.5) | / | (1144.1 / 5522.8) |
| = | 0.206001 | / | 0.207159 |
| | = | 0.9944 |
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 - (1754.4 + 1693.7) / 6754.4) | / | (1 - (1614.2 + 1798.8) / 6828.8) |
| = | 0.489503 | / | 0.500205 |
| | = | 0.9786 |
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 |
| = | 5522.8 | / | 5215.5 |
| | = | 1.0589 |
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)) |
| = | (245.2 / (245.2 + 1798.8)) | / | (268 / (268 + 1693.7)) |
| = | 0.119961 | / | 0.136616 |
| | = | 0.8781 |
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) |
| = | (661.8 / 5522.8) | / | (585.5 / 5215.5) |
| = | 0.119831 | / | 0.112262 |
| | = | 1.0674 |
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) |
| = | ((2529.1 + 1385.8) / 6754.4) | / | ((3097.5 + 1026.4) / 6828.8) |
| = | 0.579607 | / | 0.603898 |
| | = | 0.9598 |
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 |
| = | (213.1 - -7.8 | - | 369.6) | / | 6754.4 |
| | = | -0.022015 |
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.
Greif has a M-score of -2.57 suggests that the company is unlikely to be a manipulator.
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