METRO AG Beneish M-Score Historical Data
The historical data trend for METRO AG'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.
METRO AG Beneish M-Score Chart
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METRO AG Annual Data
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Trend |
Sep14 |
Sep15 |
Sep16 |
Sep17 |
Sep18 |
Sep19 |
Sep20 |
Sep21 |
Sep22 |
Sep23 |
| Beneish M-Score |
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-2.67 |
-2.28 |
-3.24 |
-2.39 |
-2.50 |
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METRO AG Quarterly Data
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Dec18 |
Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
| Beneish M-Score |
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-2.39 |
-2.33 |
-2.30 |
-2.16 |
-2.50 |
Competitive Comparison of METRO AG's Beneish M-Score
For the Food Distribution subindustry, METRO AG'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.
METRO AG's Beneish M-Score Distribution in the Retail - Defensive Industry
For the Retail - Defensive industry and Consumer Defensive sector, METRO AG's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where METRO AG's Beneish M-Score falls into.
METRO AG 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 METRO AG 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 * 1.0436 | + | 0.528 * 1.0596 | + | 0.404 * 1.0209 | + | 0.892 * 1.0268 | + | 0.115 * 0.9356 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9988 | + | 4.679 * -0.02421 | - | 0.327 * 1.0125 |
| = | -2.50 |
* 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 (Sep23) TTM: | Last Year (Sep22) TTM: |
Total Receivables was €914 Mil.
Revenue was 7904 + 7642 + 6897 + 8107 = €30,550 Mil.
Gross Profit was 1259 + 1230 + 1020 + 1374 = €4,883 Mil.
Total Current Assets was €4,718 Mil.
Total Assets was €11,648 Mil.
Property, Plant and Equipment(Net PPE) was €5,091 Mil.
Depreciation, Depletion and Amortization(DDA) was €936 Mil.
Selling, General, & Admin. Expense(SGA) was €2,609 Mil.
Total Current Liabilities was €6,100 Mil.
Long-Term Debt & Capital Lease Obligation was €2,838 Mil.
Net Income was -150 + 174 + -107 + 522 = €439 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = €0 Mil.
Cash Flow from Operations was 505 + 656 + -583 + 143 = €721 Mil.
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Total Receivables was €853 Mil.
Revenue was 7993 + 7911 + 6245 + 7604 = €29,753 Mil.
Gross Profit was 1301 + 1363 + 1009 + 1366 = €5,039 Mil.
Total Current Assets was €5,132 Mil.
Total Assets was €12,855 Mil.
Property, Plant and Equipment(Net PPE) was €5,735 Mil.
Depreciation, Depletion and Amortization(DDA) was €975 Mil.
Selling, General, & Admin. Expense(SGA) was €2,544 Mil.
Total Current Liabilities was €6,677 Mil.
Long-Term Debt & Capital Lease Obligation was €3,065 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) |
| = | (914 / 30550) | / | (853 / 29753) |
| = | 0.029918 | / | 0.028669 |
| | = | 1.0436 |
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) |
| = | (5039 / 29753) | / | (4883 / 30550) |
| = | 0.169361 | / | 0.159836 |
| | = | 1.0596 |
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 - (4718 + 5091) / 11648) | / | (1 - (5132 + 5735) / 12855) |
| = | 0.157881 | / | 0.154648 |
| | = | 1.0209 |
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 |
| = | 30550 | / | 29753 |
| | = | 1.0268 |
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)) |
| = | (975 / (975 + 5735)) | / | (936 / (936 + 5091)) |
| = | 0.145306 | / | 0.155301 |
| | = | 0.9356 |
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) |
| = | (2609 / 30550) | / | (2544 / 29753) |
| = | 0.085401 | / | 0.085504 |
| | = | 0.9988 |
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) |
| = | ((2838 + 6100) / 11648) | / | ((3065 + 6677) / 12855) |
| = | 0.767342 | / | 0.757837 |
| | = | 1.0125 |
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 |
| = | (439 - 0 | - | 721) | / | 11648 |
| | = | -0.02421 |
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.
METRO AG has a M-score of -2.50 suggests that the company is unlikely to be a manipulator.
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