Palantir Technologies Beneish M-Score Historical Data
The historical data trend for Palantir Technologies'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.
Palantir Technologies Beneish M-Score Chart
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Palantir Technologies Annual Data
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Dec18 |
Dec19 |
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Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
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-3.44 |
-2.64 |
-2.73 |
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Palantir Technologies Quarterly Data
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Dec18 |
Jun19 |
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Dec23 |
| Beneish M-Score |
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-2.64 |
-2.98 |
-2.60 |
-2.65 |
-2.73 |
Competitive Comparison of Palantir Technologies's Beneish M-Score
For the Software - Infrastructure subindustry, Palantir Technologies'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.
Palantir Technologies's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Palantir Technologies's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Palantir Technologies's Beneish M-Score falls into.
Palantir Technologies 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 Palantir Technologies 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 * 1.2095 | + | 0.528 * 0.9744 | + | 0.404 * 0.7803 | + | 0.892 * 1.1675 | + | 0.115 * 0.6106 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8371 | + | 4.679 * -0.108433 | - | 0.327 * 0.89 |
| = | -2.73 |
* 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 $365 Mil.
Revenue was 608.35 + 558.159 + 533.317 + 525.186 = $2,225 Mil.
Gross Profit was 499.711 + 450.237 + 426.418 + 417.541 = $1,794 Mil.
Total Current Assets was $4,139 Mil.
Total Assets was $4,522 Mil.
Property, Plant and Equipment(Net PPE) was $231 Mil.
Depreciation, Depletion and Amortization(DDA) was $33 Mil.
Selling, General, & Admin. Expense(SGA) was $1,269 Mil.
Total Current Liabilities was $746 Mil.
Long-Term Debt & Capital Lease Obligation was $175 Mil.
Net Income was 93.391 + 71.505 + 28.127 + 16.802 = $210 Mil.
Non Operating Income was -3.956 + 3.864 + -9.024 + -2.861 = $-12 Mil.
Cash Flow from Operations was 301.172 + 133.443 + 90.192 + 187.376 = $712 Mil.
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Total Receivables was $258 Mil.
Revenue was 508.624 + 477.88 + 473.01 + 446.357 = $1,906 Mil.
Gross Profit was 404.313 + 370.269 + 370.786 + 351.954 = $1,497 Mil.
Total Current Assets was $3,042 Mil.
Total Assets was $3,461 Mil.
Property, Plant and Equipment(Net PPE) was $269 Mil.
Depreciation, Depletion and Amortization(DDA) was $23 Mil.
Selling, General, & Admin. Expense(SGA) was $1,299 Mil.
Total Current Liabilities was $588 Mil.
Long-Term Debt & Capital Lease Obligation was $204 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) |
| = | (364.784 / 2225.012) | / | (258.346 / 1905.871) |
| = | 0.163947 | / | 0.135553 |
| | = | 1.2095 |
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) |
| = | (1497.322 / 1905.871) | / | (1793.907 / 2225.012) |
| = | 0.785637 | / | 0.806246 |
| | = | 0.9744 |
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 - (4138.618 + 230.621) / 4522.425) | / | (1 - (3041.577 + 269.41) / 3461.239) |
| = | 0.033873 | / | 0.04341 |
| | = | 0.7803 |
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 |
| = | 2225.012 | / | 1905.871 |
| | = | 1.1675 |
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)) |
| = | (22.522 / (22.522 + 269.41)) | / | (33.354 / (33.354 + 230.621)) |
| = | 0.077148 | / | 0.126353 |
| | = | 0.6106 |
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) |
| = | (1269.317 / 2225.012) | / | (1298.844 / 1905.871) |
| = | 0.570476 | / | 0.681496 |
| | = | 0.8371 |
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) |
| = | ((175.216 + 746.018) / 4522.425) | / | ((204.305 + 587.941) / 3461.239) |
| = | 0.203704 | / | 0.228891 |
| | = | 0.89 |
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 |
| = | (209.825 - -11.977 | - | 712.183) | / | 4522.425 |
| | = | -0.108433 |
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.
Palantir Technologies has a M-score of -2.73 suggests that the company is unlikely to be a manipulator.
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