Nikola Beneish M-Score Historical Data
The historical data trend for Nikola'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.
Nikola Beneish M-Score Chart
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Nikola Annual Data
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Trend |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
- |
- |
- |
-4.62 |
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Nikola Quarterly Data
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Dec18 |
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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22.30 |
-2.49 |
-5.44 |
-4.62 |
Competitive Comparison of Nikola's Beneish M-Score
For the Farm & Heavy Construction Machinery subindustry, Nikola'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.
Nikola's Beneish M-Score Distribution in the Farm & Heavy Construction Machinery Industry
For the Farm & Heavy Construction Machinery industry and Industrials sector, Nikola's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Nikola's Beneish M-Score falls into.
Nikola 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 Nikola 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 * 0.8632 | + | 0.528 * 0.2797 | + | 0.404 * 0.5055 | + | 0.892 * 0.7296 | + | 0.115 * 0.7765 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8306 | + | 4.679 * -0.272813 | - | 0.327 * 0.7622 |
| = | -4.62 |
* 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 $27.20 Mil.
Revenue was 11.532 + -1.732 + 15.362 + 11.117 = $36.28 Mil.
Gross Profit was -38.236 + -125.503 + -27.631 + -32.91 = $-224.28 Mil.
Total Current Assets was $572.41 Mil.
Total Assets was $1,274.86 Mil.
Property, Plant and Equipment(Net PPE) was $503.42 Mil.
Depreciation, Depletion and Amortization(DDA) was $35.89 Mil.
Selling, General, & Admin. Expense(SGA) was $209.78 Mil.
Total Current Liabilities was $260.11 Mil.
Long-Term Debt & Capital Lease Obligation was $274.04 Mil.
Net Income was -153.596 + -425.764 + -217.828 + -169.094 = $-966.28 Mil.
Non Operating Income was -20.857 + -146.654 + 44.982 + 0.222 = $-122.31 Mil.
Cash Flow from Operations was -117.754 + -91.259 + -107.204 + -179.961 = $-496.18 Mil.
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Total Receivables was $43.19 Mil.
Revenue was 5.463 + 24.241 + 18.134 + 1.887 = $49.73 Mil.
Gross Profit was -26.974 + -30.169 + -29.257 + 0.431 = $-85.97 Mil.
Total Current Assets was $436.93 Mil.
Total Assets was $1,236.66 Mil.
Property, Plant and Equipment(Net PPE) was $417.79 Mil.
Depreciation, Depletion and Amortization(DDA) was $22.77 Mil.
Selling, General, & Admin. Expense(SGA) was $346.19 Mil.
Total Current Liabilities was $383.59 Mil.
Long-Term Debt & Capital Lease Obligation was $296.22 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) |
| = | (27.199 / 36.279) | / | (43.189 / 49.725) |
| = | 0.749717 | / | 0.868557 |
| | = | 0.8632 |
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) |
| = | (-85.969 / 49.725) | / | (-224.28 / 36.279) |
| = | -1.728889 | / | -6.182089 |
| | = | 0.2797 |
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 - (572.412 + 503.416) / 1274.857) | / | (1 - (436.926 + 417.785) / 1236.658) |
| = | 0.156119 | / | 0.308854 |
| | = | 0.5055 |
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 |
| = | 36.279 | / | 49.725 |
| | = | 0.7296 |
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)) |
| = | (22.765 / (22.765 + 417.785)) | / | (35.89 / (35.89 + 503.416)) |
| = | 0.051674 | / | 0.066548 |
| | = | 0.7765 |
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) |
| = | (209.78 / 36.279) | / | (346.186 / 49.725) |
| = | 5.782409 | / | 6.962011 |
| | = | 0.8306 |
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) |
| = | ((274.044 + 260.105) / 1274.857) | / | ((296.219 + 383.59) / 1236.658) |
| = | 0.418987 | / | 0.549715 |
| | = | 0.7622 |
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 |
| = | (-966.282 - -122.307 | - | -496.178) | / | 1274.857 |
| | = | -0.272813 |
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.
Nikola has a M-score of -4.62 suggests that the company is unlikely to be a manipulator.
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