Eurocash Beneish M-Score Historical Data
The historical data trend for Eurocash'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.
Eurocash Beneish M-Score Chart
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Eurocash Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.87 |
-2.87 |
-2.87 |
-2.77 |
-3.10 |
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Eurocash Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-2.80 |
-2.89 |
-2.81 |
-3.10 |
-3.07 |
Competitive Comparison of Eurocash's Beneish M-Score
For the Grocery Stores subindustry, Eurocash'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.
Eurocash's Beneish M-Score Distribution in the Retail - Defensive Industry
For the Retail - Defensive industry and Consumer Defensive sector, Eurocash's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Eurocash's Beneish M-Score falls into.
Eurocash 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 Eurocash 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 * 0.9361 | + | 0.528 * 1.0055 | + | 0.404 * 0.9553 | + | 0.892 * 1.018 | + | 0.115 * 0.9927 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9966 | + | 4.679 * -0.113794 | - | 0.327 * 1 |
| = | -3.07 |
* 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 (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was zł1,487 Mil.
Revenue was 7624.804 + 7920.394 + 8570.165 + 8378.842 = zł32,494 Mil.
Gross Profit was 1008.046 + 1147.366 + 1148.456 + 1093.851 = zł4,398 Mil.
Total Current Assets was zł3,535 Mil.
Total Assets was zł8,784 Mil.
Property, Plant and Equipment(Net PPE) was zł2,700 Mil.
Depreciation, Depletion and Amortization(DDA) was zł638 Mil.
Selling, General, & Admin. Expense(SGA) was zł1,650 Mil.
Total Current Liabilities was zł5,542 Mil.
Long-Term Debt & Capital Lease Obligation was zł2,238 Mil.
Net Income was -86.8 + 82.547 + 29.962 + 38.338 = zł64 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = zł0 Mil.
Cash Flow from Operations was 43.941 + 357.787 + 355.546 + 306.344 = zł1,064 Mil.
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Total Receivables was zł1,560 Mil.
Revenue was 7588.396 + 8222.659 + 8268.351 + 7838.764 = zł31,918 Mil.
Gross Profit was 1019.563 + 1151.284 + 1114.58 + 1058.116 = zł4,344 Mil.
Total Current Assets was zł3,391 Mil.
Total Assets was zł8,539 Mil.
Property, Plant and Equipment(Net PPE) was zł2,555 Mil.
Depreciation, Depletion and Amortization(DDA) was zł599 Mil.
Selling, General, & Admin. Expense(SGA) was zł1,626 Mil.
Total Current Liabilities was zł5,759 Mil.
Long-Term Debt & Capital Lease Obligation was zł1,804 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) |
| = | (1486.568 / 32494.205) | / | (1559.881 / 31918.17) |
| = | 0.045749 | / | 0.048871 |
| | = | 0.9361 |
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) |
| = | (4343.543 / 31918.17) | / | (4397.719 / 32494.205) |
| = | 0.136084 | / | 0.135339 |
| | = | 1.0055 |
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 - (3535.246 + 2700.148) / 8784.025) | / | (1 - (3390.871 + 2554.829) / 8539.168) |
| = | 0.290144 | / | 0.303714 |
| | = | 0.9553 |
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 |
| = | 32494.205 | / | 31918.17 |
| | = | 1.018 |
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)) |
| = | (598.538 / (598.538 + 2554.829)) | / | (638.345 / (638.345 + 2700.148)) |
| = | 0.189809 | / | 0.191208 |
| | = | 0.9927 |
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) |
| = | (1649.631 / 32494.205) | / | (1625.889 / 31918.17) |
| = | 0.050767 | / | 0.050939 |
| | = | 0.9966 |
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) |
| = | ((2238.281 + 5541.64) / 8784.025) | / | ((1804.178 + 5759.15) / 8539.168) |
| = | 0.88569 | / | 0.885722 |
| | = | 1 |
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 |
| = | (64.047 - 0 | - | 1063.618) | / | 8784.025 |
| | = | -0.113794 |
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.
Eurocash has a M-score of -3.07 suggests that the company is unlikely to be a manipulator.
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