Metro Beneish M-Score Historical Data
The historical data trend for Metro'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 Beneish M-Score Chart
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Metro Annual Data
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Trend |
Sep14 |
Sep15 |
Sep16 |
Sep17 |
Sep18 |
Sep19 |
Sep20 |
Sep21 |
Sep22 |
Sep23 |
| Beneish M-Score |
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-2.24 |
-2.81 |
-2.67 |
-2.64 |
-2.42 |
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Metro 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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-2.62 |
-2.52 |
-2.58 |
-2.42 |
-2.40 |
Competitive Comparison of Metro's Beneish M-Score
For the Grocery Stores subindustry, Metro'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's Beneish M-Score Distribution in the Retail - Defensive Industry
For the Retail - Defensive industry and Consumer Defensive sector, Metro's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Metro's Beneish M-Score falls into.
Metro 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 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 * 1.0478 | + | 0.528 * 1.0133 | + | 0.404 * 0.9611 | + | 0.892 * 1.0614 | + | 0.115 * 1.0443 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0 | + | 4.679 * -0.036261 | - | 0.327 * 1.0084 |
| = | -2.39 |
* 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 $715 Mil.
Revenue was 3707.662 + 3748.208 + 4837.799 + 3328.583 = $15,622 Mil.
Gross Profit was 725.477 + 730.471 + 950.399 + 668.932 = $3,075 Mil.
Total Current Assets was $1,978 Mil.
Total Assets was $10,509 Mil.
Property, Plant and Equipment(Net PPE) was $3,528 Mil.
Depreciation, Depletion and Amortization(DDA) was $398 Mil.
Selling, General, & Admin. Expense(SGA) was $0 Mil.
Total Current Liabilities was $1,707 Mil.
Long-Term Debt & Capital Lease Obligation was $2,912 Mil.
Net Income was 169.201 + 163.772 + 259.672 + 159.614 = $752 Mil.
Non Operating Income was 0.894 + -0.074 + 0.151 + -0.219 = $1 Mil.
Cash Flow from Operations was 128.429 + 286.084 + 410.884 + 307.169 = $1,133 Mil.
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Total Receivables was $643 Mil.
Revenue was 3438.278 + 3323.038 + 4580.99 + 3376.145 = $14,718 Mil.
Gross Profit was 674.126 + 679.436 + 904.952 + 677.251 = $2,936 Mil.
Total Current Assets was $1,783 Mil.
Total Assets was $10,067 Mil.
Property, Plant and Equipment(Net PPE) was $3,297 Mil.
Depreciation, Depletion and Amortization(DDA) was $391 Mil.
Selling, General, & Admin. Expense(SGA) was $583 Mil.
Total Current Liabilities was $1,494 Mil.
Long-Term Debt & Capital Lease Obligation was $2,894 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) |
| = | (714.595 / 15622.252) | / | (642.547 / 14718.451) |
| = | 0.045742 | / | 0.043656 |
| | = | 1.0478 |
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) |
| = | (2935.765 / 14718.451) | / | (3075.279 / 15622.252) |
| = | 0.199462 | / | 0.196852 |
| | = | 1.0133 |
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 - (1977.937 + 3527.579) / 10508.795) | / | (1 - (1783.29 + 3296.945) / 10066.838) |
| = | 0.476104 | / | 0.495349 |
| | = | 0.9611 |
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 |
| = | 15622.252 | / | 14718.451 |
| | = | 1.0614 |
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)) |
| = | (390.529 / (390.529 + 3296.945)) | / | (398.142 / (398.142 + 3527.579)) |
| = | 0.105907 | / | 0.101419 |
| | = | 1.0443 |
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) |
| = | (0 / 15622.252) | / | (582.77 / 14718.451) |
| = | 0 | / | 0.039595 |
| | = | 0 |
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) |
| = | ((2911.822 + 1706.694) / 10508.795) | / | ((2894.001 + 1493.633) / 10066.838) |
| = | 0.439491 | / | 0.43585 |
| | = | 1.0084 |
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 |
| = | (752.259 - 0.752 | - | 1132.566) | / | 10508.795 |
| | = | -0.036261 |
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 has a M-score of -2.39 suggests that the company is unlikely to be a manipulator.
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