Netflix Beneish M-Score Historical Data
The historical data trend for Netflix'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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Netflix Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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|
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|
|
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-1.80 |
-2.13 |
-1.67 |
-1.33 |
-2.56 |
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Netflix 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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-1.33 |
-2.12 |
-2.01 |
-2.37 |
-2.56 |
Competitive Comparison
For the Entertainment subindustry, Netflix'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.
Netflix Beneish M-Score Distribution
For the Media - Diversified industry and Communication Services sector, Netflix's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Netflix's Beneish M-Score falls into.
Netflix 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 Netflix 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 * 1.0882 | + | 0.528 * 0.9478 | + | 0.404 * 0.9812 | + | 0.892 * 1.0667 | + | 0.115 * 1.0047 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0003 | + | 4.679 * -0.038297 | - | 0.327 * 1.0294 |
| = | -2.56 |
* 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 $1,842 Mil.
Revenue was 8832.825 + 8541.668 + 8187.301 + 8161.503 = $33,723 Mil.
Gross Profit was 3525.34 + 3610.88 + 3513.831 + 3357.878 = $14,008 Mil.
Total Current Assets was $9,918 Mil.
Total Assets was $48,732 Mil.
Property, Plant and Equipment(Net PPE) was $1,491 Mil.
Depreciation, Depletion and Amortization(DDA) was $14,554 Mil.
Selling, General, & Admin. Expense(SGA) was $4,378 Mil.
Total Current Liabilities was $8,861 Mil.
Long-Term Debt & Capital Lease Obligation was $14,143 Mil.
Net Income was 937.838 + 1677.422 + 1487.61 + 1305.12 = $5,408 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = $0 Mil.
Cash Flow from Operations was 1663.014 + 1992.315 + 1440.232 + 2178.74 = $7,274 Mil.
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Total Receivables was $1,587 Mil.
Revenue was 7852.053 + 7925.589 + 7970.141 + 7867.767 = $31,616 Mil.
Gross Profit was 2447.893 + 3136.924 + 3279.386 + 3583.062 = $12,447 Mil.
Total Current Assets was $9,266 Mil.
Total Assets was $48,595 Mil.
Property, Plant and Equipment(Net PPE) was $1,398 Mil.
Depreciation, Depletion and Amortization(DDA) was $14,363 Mil.
Selling, General, & Admin. Expense(SGA) was $4,103 Mil.
Total Current Liabilities was $7,931 Mil.
Long-Term Debt & Capital Lease Obligation was $14,353 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) |
| = | (1842.054 / 33723.297) | / | (1586.898 / 31615.55) |
| = | 0.054623 | / | 0.050194 |
| | = | 1.0882 |
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) |
| = | (12447.265 / 31615.55) | / | (14007.929 / 33723.297) |
| = | 0.393707 | / | 0.415378 |
| | = | 0.9478 |
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 - (9918.133 + 1491.444) / 48731.992) | / | (1 - (9266.473 + 1398.257) / 48594.768) |
| = | 0.765871 | / | 0.780537 |
| | = | 0.9812 |
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 |
| = | 33723.297 | / | 31615.55 |
| | = | 1.0667 |
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)) |
| = | (14362.814 / (14362.814 + 1398.257)) | / | (14554.384 / (14554.384 + 1491.444)) |
| = | 0.911284 | / | 0.907051 |
| | = | 1.0047 |
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) |
| = | (4378.168 / 33723.297) | / | (4103.393 / 31615.55) |
| = | 0.129826 | / | 0.12979 |
| | = | 1.0003 |
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) |
| = | ((14143.417 + 8860.655) / 48731.992) | / | ((14353.076 + 7930.974) / 48594.768) |
| = | 0.472053 | / | 0.458569 |
| | = | 1.0294 |
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 |
| = | (5407.99 - 0 | - | 7274.301) | / | 48731.992 |
| | = | -0.038297 |
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.
Netflix has a M-score of -2.56 suggests that the company is unlikely to be a manipulator.
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