DocuSign Beneish M-Score Historical Data
The historical data trend for DocuSign'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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DocuSign Annual Data
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Trend |
Jan16 |
Jan17 |
Jan18 |
Jan19 |
Jan20 |
Jan21 |
Jan22 |
Jan23 |
Jan24 |
| Beneish M-Score |
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-2.85 |
-3.26 |
-3.25 |
-3.20 |
-3.88 |
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DocuSign Quarterly Data
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Apr19 |
Jul19 |
Oct19 |
Jan20 |
Apr20 |
Jul20 |
Oct20 |
Jan21 |
Apr21 |
Jul21 |
Oct21 |
Jan22 |
Apr22 |
Jul22 |
Oct22 |
Jan23 |
Apr23 |
Jul23 |
Oct23 |
Jan24 |
| Beneish M-Score |
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-3.20 |
-3.02 |
-3.15 |
-3.67 |
-3.88 |
Competitive Comparison
For the Software - Application subindustry, DocuSign'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.
DocuSign Beneish M-Score Distribution
For the Software industry and Technology sector, DocuSign's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where DocuSign's Beneish M-Score falls into.
DocuSign 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 DocuSign 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 * 0.7834 | + | 0.528 * 0.9927 | + | 0.404 * 1.009 | + | 0.892 * 1.0978 | + | 0.115 * 0.9833 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9278 | + | 4.679 * -0.29454 | - | 0.327 * 0.7687 |
| = | -3.88 |
* 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 (Jan24) TTM: | Last Year (Jan23) TTM: |
Total Receivables was $455 Mil.
Revenue was 712.386 + 700.421 + 687.687 + 661.388 = $2,762 Mil.
Gross Profit was 564.479 + 557.776 + 542.105 + 524.901 = $2,189 Mil.
Total Current Assets was $1,568 Mil.
Total Assets was $2,971 Mil.
Property, Plant and Equipment(Net PPE) was $368 Mil.
Depreciation, Depletion and Amortization(DDA) was $95 Mil.
Selling, General, & Admin. Expense(SGA) was $1,588 Mil.
Total Current Liabilities was $1,661 Mil.
Long-Term Debt & Capital Lease Obligation was $121 Mil.
Net Income was 27.241 + 38.805 + 7.395 + 0.539 = $74 Mil.
Non Operating Income was -0.088 + -0.71 + -0.811 + -28.772 = $-30 Mil.
Cash Flow from Operations was 270.698 + 264.177 + 211.016 + 233.635 = $980 Mil.
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Total Receivables was $529 Mil.
Revenue was 659.576 + 645.463 + 622.184 + 588.692 = $2,516 Mil.
Gross Profit was 522.15 + 515.921 + 485.48 + 456.276 = $1,980 Mil.
Total Current Assets was $1,631 Mil.
Total Assets was $3,013 Mil.
Property, Plant and Equipment(Net PPE) was $341 Mil.
Depreciation, Depletion and Amortization(DDA) was $86 Mil.
Selling, General, & Admin. Expense(SGA) was $1,559 Mil.
Total Current Liabilities was $2,208 Mil.
Long-Term Debt & Capital Lease Obligation was $141 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) |
| = | (455.221 / 2761.882) | / | (529.351 / 2515.915) |
| = | 0.164823 | / | 0.210401 |
| | = | 0.7834 |
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) |
| = | (1979.827 / 2515.915) | / | (2189.261 / 2761.882) |
| = | 0.786921 | / | 0.79267 |
| | = | 0.9927 |
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 - (1567.667 + 368.361) / 2971.29) | / | (1 - (1631.004 + 341.385) / 3012.72) |
| = | 0.348422 | / | 0.345313 |
| | = | 1.009 |
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 |
| = | 2761.882 | / | 2515.915 |
| | = | 1.0978 |
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)) |
| = | (86.255 / (86.255 + 341.385)) | / | (95.062 / (95.062 + 368.361)) |
| = | 0.2017 | / | 0.20513 |
| | = | 0.9833 |
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) |
| = | (1587.758 / 2761.882) | / | (1558.939 / 2515.915) |
| = | 0.574883 | / | 0.619631 |
| | = | 0.9278 |
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) |
| = | ((120.823 + 1660.621) / 2971.29) | / | ((141.348 + 2208.322) / 3012.72) |
| = | 0.599552 | / | 0.779916 |
| | = | 0.7687 |
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 |
| = | (73.98 - -30.381 | - | 979.526) | / | 2971.29 |
| | = | -0.29454 |
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.
DocuSign has a M-score of -3.88 suggests that the company is unlikely to be a manipulator.
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