San Miguel Beneish M-Score Historical Data
The historical data trend for San Miguel'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.
San Miguel Beneish M-Score Chart
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San Miguel Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.56 |
-2.61 |
-2.28 |
-1.73 |
-2.61 |
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San Miguel 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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-1.73 |
-2.04 |
-2.48 |
-2.53 |
-2.61 |
Competitive Comparison of San Miguel's Beneish M-Score
For the Conglomerates subindustry, San Miguel'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.
San Miguel's Beneish M-Score Distribution in the Conglomerates Industry
For the Conglomerates industry and Industrials sector, San Miguel's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where San Miguel's Beneish M-Score falls into.
San Miguel 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 San Miguel 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 * 1.1475 | + | 0.528 * 0.7736 | + | 0.404 * 1.0861 | + | 0.892 * 0.9602 | + | 0.115 * 1.3483 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1509 | + | 4.679 * -0.033707 | - | 0.327 * 0.993 |
| = | -2.61 |
* 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 $4,556 Mil.
Revenue was 6677.145 + 6508.214 + 5861.391 + 6003.742 = $25,050 Mil.
Gross Profit was 1063.245 + 1088.717 + 995.143 + 979.074 = $4,126 Mil.
Total Current Assets was $14,396 Mil.
Total Assets was $42,585 Mil.
Property, Plant and Equipment(Net PPE) was $15,137 Mil.
Depreciation, Depletion and Amortization(DDA) was $925 Mil.
Selling, General, & Admin. Expense(SGA) was $560 Mil.
Total Current Liabilities was $12,904 Mil.
Long-Term Debt & Capital Lease Obligation was $17,163 Mil.
Net Income was 0.9 + -10.58 + -139.823 + 152.931 = $3 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = $0 Mil.
Cash Flow from Operations was -1027.749 + 353.688 + 1324.451 + 788.465 = $1,439 Mil.
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Total Receivables was $4,135 Mil.
Revenue was 6823.531 + 6945.381 + 6833.609 + 5484.968 = $26,087 Mil.
Gross Profit was 860.705 + 647.931 + 911.215 + 904.462 = $3,324 Mil.
Total Current Assets was $15,312 Mil.
Total Assets was $41,416 Mil.
Property, Plant and Equipment(Net PPE) was $14,416 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,214 Mil.
Selling, General, & Admin. Expense(SGA) was $507 Mil.
Total Current Liabilities was $12,599 Mil.
Long-Term Debt & Capital Lease Obligation was $16,849 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) |
| = | (4556.056 / 25050.492) | / | (4134.647 / 26087.489) |
| = | 0.181875 | / | 0.158492 |
| | = | 1.1475 |
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) |
| = | (3324.313 / 26087.489) | / | (4126.179 / 25050.492) |
| = | 0.127429 | / | 0.164714 |
| | = | 0.7736 |
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 - (14396.203 + 15137.032) / 42585.316) | / | (1 - (15312.127 + 14416.116) / 41415.822) |
| = | 0.306493 | / | 0.282201 |
| | = | 1.0861 |
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 |
| = | 25050.492 | / | 26087.489 |
| | = | 0.9602 |
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)) |
| = | (1213.857 / (1213.857 + 14416.116)) | / | (925.223 / (925.223 + 15137.032)) |
| = | 0.077662 | / | 0.057602 |
| | = | 1.3483 |
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) |
| = | (559.899 / 25050.492) | / | (506.653 / 26087.489) |
| = | 0.022351 | / | 0.019421 |
| | = | 1.1509 |
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) |
| = | ((17162.608 + 12903.981) / 42585.316) | / | ((16848.711 + 12599.037) / 41415.822) |
| = | 0.706032 | / | 0.711027 |
| | = | 0.993 |
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 |
| = | (3.428 - 0 | - | 1438.855) | / | 42585.316 |
| | = | -0.033707 |
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.
San Miguel has a M-score of -2.61 suggests that the company is unlikely to be a manipulator.
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