Tesla Beneish M-Score Historical Data
The historical data trend for Tesla'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.
Tesla Beneish M-Score Chart
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Tesla Annual Data
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Trend |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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-2.71 |
-2.47 |
-2.04 |
-1.63 |
-2.58 |
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Tesla Quarterly Data
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Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
Mar25 |
| Beneish M-Score |
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-1.63 |
-1.99 |
-1.97 |
-2.58 |
-2.89 |
Competitive Comparison of Tesla's Beneish M-Score
For the Auto Manufacturers subindustry, Tesla'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.
Tesla's Beneish M-Score Distribution in the Vehicles & Parts Industry
For the Vehicles & Parts industry and Consumer Cyclical sector, Tesla's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Tesla's Beneish M-Score falls into.
Tesla 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 Tesla 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 * 0.963 | + | 0.528 * 1.0066 | + | 0.404 * 0.9445 | + | 0.892 * 1.0103 | + | 0.115 * 0.9884 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.976 | + | 4.679 * -0.080864 | - | 0.327 * 0.9599 |
| = | -2.89 |
* 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 (Mar25) TTM: | Last Year (Mar24) TTM: |
Total Receivables was $3,782 Mil.
Revenue was 19335 + 25707 + 25182 + 25500 = $95,724 Mil.
Gross Profit was 3153 + 4179 + 4997 + 4578 = $16,907 Mil.
Total Current Assets was $59,389 Mil.
Total Assets was $125,111 Mil.
Property, Plant and Equipment(Net PPE) was $52,750 Mil.
Depreciation, Depletion and Amortization(DDA) was $5,569 Mil.
Selling, General, & Admin. Expense(SGA) was $5,027 Mil.
Total Current Liabilities was $29,753 Mil.
Long-Term Debt & Capital Lease Obligation was $10,049 Mil.
Net Income was 409 + 2356 + 2167 + 1478 = $6,410 Mil.
Non Operating Income was -213 + 830 + -325 + -602 = $-310 Mil.
Cash Flow from Operations was 2156 + 4814 + 6255 + 3612 = $16,837 Mil.
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Total Receivables was $3,887 Mil.
Revenue was 21301 + 25167 + 23350 + 24927 = $94,745 Mil.
Gross Profit was 3696 + 4438 + 4178 + 4533 = $16,845 Mil.
Total Current Assets was $50,535 Mil.
Total Assets was $109,226 Mil.
Property, Plant and Equipment(Net PPE) was $46,701 Mil.
Depreciation, Depletion and Amortization(DDA) was $4,867 Mil.
Selling, General, & Admin. Expense(SGA) was $5,098 Mil.
Total Current Liabilities was $29,453 Mil.
Long-Term Debt & Capital Lease Obligation was $6,746 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) |
| = | (3782 / 95724) | / | (3887 / 94745) |
| = | 0.039509 | / | 0.041026 |
| | = | 0.963 |
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) |
| = | (16845 / 94745) | / | (16907 / 95724) |
| = | 0.177793 | / | 0.176622 |
| | = | 1.0066 |
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 - (59389 + 52750) / 125111) | / | (1 - (50535 + 46701) / 109226) |
| = | 0.103684 | / | 0.109772 |
| | = | 0.9445 |
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 |
| = | 95724 | / | 94745 |
| | = | 1.0103 |
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)) |
| = | (4867 / (4867 + 46701)) | / | (5569 / (5569 + 52750)) |
| = | 0.09438 | / | 0.095492 |
| | = | 0.9884 |
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) |
| = | (5027 / 95724) | / | (5098 / 94745) |
| = | 0.052516 | / | 0.053808 |
| | = | 0.976 |
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) |
| = | ((10049 + 29753) / 125111) | / | ((6746 + 29453) / 109226) |
| = | 0.318133 | / | 0.331414 |
| | = | 0.9599 |
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 |
| = | (6410 - -310 | - | 16837) | / | 125111 |
| | = | -0.080864 |
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.
Tesla has a M-score of -2.89 suggests that the company is unlikely to be a manipulator.
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