Meta Platforms Beneish M-Score Historical Data
The historical data trend for Meta Platforms'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.
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Meta Platforms Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-3.52 |
-2.44 |
-2.85 |
-3.30 |
-3.02 |
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Meta Platforms 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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-3.30 |
-3.34 |
-3.30 |
-3.22 |
-3.02 |
Competitive Comparison
For the Internet Content & Information subindustry, Meta Platforms'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.
Meta Platforms Beneish M-Score Distribution
For the Interactive Media industry and Communication Services sector, Meta Platforms's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Meta Platforms's Beneish M-Score falls into.
Meta Platforms 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 Meta Platforms 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 * 1.0379 | + | 0.528 * 0.9702 | + | 0.404 * 0.8181 | + | 0.892 * 1.1569 | + | 0.115 * 0.9325 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.7569 | + | 4.679 * -0.13783 | - | 0.327 * 1.046 |
| = | -3.02 |
* 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 $16,169 Mil.
Revenue was 40111 + 34146 + 31999 + 28645 = $134,901 Mil.
Gross Profit was 32416 + 27936 + 26054 + 22537 = $108,943 Mil.
Total Current Assets was $85,365 Mil.
Total Assets was $229,623 Mil.
Property, Plant and Equipment(Net PPE) was $109,881 Mil.
Depreciation, Depletion and Amortization(DDA) was $11,178 Mil.
Selling, General, & Admin. Expense(SGA) was $23,709 Mil.
Total Current Liabilities was $31,960 Mil.
Long-Term Debt & Capital Lease Obligation was $35,611 Mil.
Net Income was 14017 + 11583 + 7788 + 5709 = $39,097 Mil.
Non Operating Income was -61 + -98 + -145 + -63 = $-367 Mil.
Cash Flow from Operations was 19404 + 20402 + 17309 + 13998 = $71,113 Mil.
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Total Receivables was $13,466 Mil.
Revenue was 32165 + 27714 + 28822 + 27908 = $116,609 Mil.
Gross Profit was 23829 + 21998 + 23630 + 21903 = $91,360 Mil.
Total Current Assets was $59,549 Mil.
Total Assets was $185,727 Mil.
Property, Plant and Equipment(Net PPE) was $92,191 Mil.
Depreciation, Depletion and Amortization(DDA) was $8,686 Mil.
Selling, General, & Admin. Expense(SGA) was $27,077 Mil.
Total Current Liabilities was $27,026 Mil.
Long-Term Debt & Capital Lease Obligation was $25,224 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) |
| = | (16169 / 134901) | / | (13466 / 116609) |
| = | 0.119858 | / | 0.11548 |
| | = | 1.0379 |
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) |
| = | (91360 / 116609) | / | (108943 / 134901) |
| = | 0.783473 | / | 0.807577 |
| | = | 0.9702 |
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 - (85365 + 109881) / 229623) | / | (1 - (59549 + 92191) / 185727) |
| = | 0.149711 | / | 0.182994 |
| | = | 0.8181 |
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 |
| = | 134901 | / | 116609 |
| | = | 1.1569 |
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)) |
| = | (8686 / (8686 + 92191)) | / | (11178 / (11178 + 109881)) |
| = | 0.086105 | / | 0.092335 |
| | = | 0.9325 |
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) |
| = | (23709 / 134901) | / | (27077 / 116609) |
| = | 0.175751 | / | 0.232203 |
| | = | 0.7569 |
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) |
| = | ((35611 + 31960) / 229623) | / | ((25224 + 27026) / 185727) |
| = | 0.294269 | / | 0.281327 |
| | = | 1.046 |
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 |
| = | (39097 - -367 | - | 71113) | / | 229623 |
| | = | -0.13783 |
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.
Meta Platforms has a M-score of -3.02 suggests that the company is unlikely to be a manipulator.
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