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 |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.47 |
-2.71 |
-2.47 |
-2.04 |
-1.63 |
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Tesla Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-2.12 |
-1.75 |
-2.05 |
-1.63 |
-1.63 |
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 * 1.1793 | + | 0.528 * 1.3012 | + | 0.404 * 1.8437 | + | 0.892 * 1.1012 | + | 0.115 * 0.9737 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1487 | + | 4.679 * 0.021076 | - | 0.327 * 0.9254 |
| = | -1.63 |
* 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 (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was ₴153,640 Mil.
Revenue was 841957.492 + 994767.579 + 922947.628 + 985281.179 = ₴3,744,954 Mil.
Gross Profit was 146090.554 + 175419.339 + 165142.406 + 179174.373 = ₴665,827 Mil.
Total Current Assets was ₴1,997,480 Mil.
Total Assets was ₴4,317,340 Mil.
Property, Plant and Equipment(Net PPE) was ₴1,845,935 Mil.
Depreciation, Depletion and Amortization(DDA) was ₴192,376 Mil.
Selling, General, & Admin. Expense(SGA) was ₴201,507 Mil.
Total Current Liabilities was ₴1,164,179 Mil.
Long-Term Debt & Capital Lease Obligation was ₴266,647 Mil.
Net Income was 44625.605 + 313446.454 + 73242.91 + 106840.576 = ₴538,156 Mil.
Non Operating Income was 4268.88 + -5731.366 + 1462.487 + 12964.746 = ₴12,965 Mil.
Cash Flow from Operations was 9565.453 + 172731.526 + 130754.208 + 121149.228 = ₴434,200 Mil.
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Total Receivables was ₴118,303 Mil.
Revenue was 922117.568 + 961209.44 + 848005.071 + 669344.546 = ₴3,400,677 Mil.
Gross Profit was 178304.786 + 228345.544 + 212732.511 + 167355.9 = ₴786,739 Mil.
Total Current Assets was ₴1,699,528 Mil.
Total Assets was ₴3,432,219 Mil.
Property, Plant and Equipment(Net PPE) was ₴1,528,338 Mil.
Depreciation, Depletion and Amortization(DDA) was ₴154,668 Mil.
Selling, General, & Admin. Expense(SGA) was ₴159,292 Mil.
Total Current Liabilities was ₴1,084,454 Mil.
Long-Term Debt & Capital Lease Obligation was ₴144,707 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) |
| = | (153640.147 / 3744953.878) | / | (118303.308 / 3400676.625) |
| = | 0.041026 | / | 0.034788 |
| | = | 1.1793 |
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) |
| = | (786738.741 / 3400676.625) | / | (665826.672 / 3744953.878) |
| = | 0.231348 | / | 0.177793 |
| | = | 1.3012 |
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 - (1997480.017 + 1845934.783) / 4317339.514) | / | (1 - (1699528.016 + 1528338.03) / 3432218.904) |
| = | 0.109772 | / | 0.05954 |
| | = | 1.8437 |
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 |
| = | 3744953.878 | / | 3400676.625 |
| | = | 1.1012 |
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)) |
| = | (154667.841 / (154667.841 + 1528338.03)) | / | (192376.278 / (192376.278 + 1845934.783)) |
| = | 0.0919 | / | 0.09438 |
| | = | 0.9737 |
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) |
| = | (201506.938 / 3744953.878) | / | (159292.46 / 3400676.625) |
| = | 0.053808 | / | 0.046841 |
| | = | 1.1487 |
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) |
| = | ((266646.882 + 1164178.865) / 4317339.514) | / | ((144707.121 + 1084453.582) / 3432218.904) |
| = | 0.331414 | / | 0.358124 |
| | = | 0.9254 |
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 |
| = | (538155.545 - 12964.747 | - | 434200.415) | / | 4317339.514 |
| | = | 0.021076 |
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 -1.63 signals that the company is likely to be a manipulator.
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