Doximity Beneish M-Score Historical Data
The historical data trend for Doximity'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.
Doximity Beneish M-Score Chart
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Doximity Annual Data
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Trend |
Mar19 |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
Mar24 |
| Beneish M-Score |
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- |
- |
-1.74 |
-2.30 |
-2.63 |
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Doximity Quarterly Data
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Mar19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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-2.52 |
-2.35 |
-2.63 |
-2.21 |
-2.46 |
Competitive Comparison of Doximity's Beneish M-Score
For the Health Information Services subindustry, Doximity'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.
Doximity's Beneish M-Score Distribution in the Healthcare Providers & Services Industry
For the Healthcare Providers & Services industry and Healthcare sector, Doximity's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Doximity's Beneish M-Score falls into.
Doximity 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 Doximity 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 * 1.1134 | + | 0.528 * 0.9801 | + | 0.404 * 0.9168 | + | 0.892 * 1.1529 | + | 0.115 * 0.9638 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9114 | + | 4.679 * -0.041842 | - | 0.327 * 0.9657 |
| = | -2.46 |
* 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 (Sep24) TTM: | Last Year (Sep23) TTM: |
Total Receivables was $124.8 Mil.
Revenue was 136.832 + 126.676 + 118.057 + 135.284 = $516.8 Mil.
Gross Profit was 123.156 + 113.126 + 105.49 + 123.094 = $464.9 Mil.
Total Current Assets was $957.7 Mil.
Total Assets was $1,118.5 Mil.
Property, Plant and Equipment(Net PPE) was $22.6 Mil.
Depreciation, Depletion and Amortization(DDA) was $10.2 Mil.
Selling, General, & Admin. Expense(SGA) was $177.1 Mil.
Total Current Liabilities was $132.3 Mil.
Long-Term Debt & Capital Lease Obligation was $11.3 Mil.
Net Income was 44.154 + 41.377 + 40.618 + 47.956 = $174.1 Mil.
Non Operating Income was -2.387 + -0.052 + 0.073 + -0.315 = $-2.7 Mil.
Cash Flow from Operations was 68.346 + 41.243 + 63.944 + 50.054 = $223.6 Mil.
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Total Receivables was $97.2 Mil.
Revenue was 113.612 + 108.469 + 110.966 + 115.262 = $448.3 Mil.
Gross Profit was 100.853 + 95.316 + 97.289 + 101.736 = $395.2 Mil.
Total Current Assets was $862.8 Mil.
Total Assets was $1,025.6 Mil.
Property, Plant and Equipment(Net PPE) was $24.5 Mil.
Depreciation, Depletion and Amortization(DDA) was $10.5 Mil.
Selling, General, & Admin. Expense(SGA) was $168.5 Mil.
Total Current Liabilities was $123.2 Mil.
Long-Term Debt & Capital Lease Obligation was $13.1 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) |
| = | (124.793 / 516.849) | / | (97.217 / 448.309) |
| = | 0.24145 | / | 0.216853 |
| | = | 1.1134 |
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) |
| = | (395.194 / 448.309) | / | (464.866 / 516.849) |
| = | 0.881521 | / | 0.899423 |
| | = | 0.9801 |
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 - (957.712 + 22.592) / 1118.516) | / | (1 - (862.82 + 24.523) / 1025.571) |
| = | 0.123567 | / | 0.134782 |
| | = | 0.9168 |
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 |
| = | 516.849 | / | 448.309 |
| | = | 1.1529 |
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)) |
| = | (10.532 / (10.532 + 24.523)) | / | (10.232 / (10.232 + 22.592)) |
| = | 0.300442 | / | 0.311723 |
| | = | 0.9638 |
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) |
| = | (177.056 / 516.849) | / | (168.509 / 448.309) |
| = | 0.342568 | / | 0.375877 |
| | = | 0.9114 |
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) |
| = | ((11.269 + 132.283) / 1118.516) | / | ((13.119 + 123.181) / 1025.571) |
| = | 0.128341 | / | 0.132902 |
| | = | 0.9657 |
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 |
| = | (174.105 - -2.681 | - | 223.587) | / | 1118.516 |
| | = | -0.041842 |
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.
Doximity has a M-score of -2.46 suggests that the company is unlikely to be a manipulator.
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