eHealth Beneish M-Score Historical Data
The historical data trend for eHealth'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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eHealth Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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|
|
|
|
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-0.74 |
-1.51 |
-1.90 |
-2.86 |
-2.59 |
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eHealth Quarterly Data
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Mar19 |
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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|
|
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|
|
|
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-2.86 |
-2.62 |
-2.79 |
-2.78 |
-2.59 |
Competitive Comparison
For the Insurance Brokers subindustry, eHealth'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.
eHealth Beneish M-Score Distribution
For the Insurance industry and Financial Services sector, eHealth's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where eHealth's Beneish M-Score falls into.
eHealth 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 eHealth 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 * 0.907 | + | 0.528 * 0.9998 | + | 0.404 * 1.0344 | + | 0.892 * 1.1172 | + | 0.115 * 0.9486 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8722 | + | 4.679 * -0.027822 | - | 0.327 * 1.0847 |
| = | -2.59 |
* 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 $248.7 Mil.
Revenue was 247.662 + 64.718 + 66.768 + 73.723 = $452.9 Mil.
Gross Profit was 246.553 + 64.524 + 66.515 + 73.508 = $451.1 Mil.
Total Current Assets was $382.4 Mil.
Total Assets was $1,113.3 Mil.
Property, Plant and Equipment(Net PPE) was $27.6 Mil.
Depreciation, Depletion and Amortization(DDA) was $19.9 Mil.
Selling, General, & Admin. Expense(SGA) was $260.1 Mil.
Total Current Liabilities was $78.5 Mil.
Long-Term Debt & Capital Lease Obligation was $96.1 Mil.
Net Income was 52.19 + -37.025 + -23.501 + -19.878 = $-28.2 Mil.
Non Operating Income was 10.075 + -0.138 + 0.108 + -0.592 = $9.5 Mil.
Cash Flow from Operations was -33.386 + -24.681 + -9.428 + 60.803 = $-6.7 Mil.
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Total Receivables was $245.4 Mil.
Revenue was 196.321 + 53.376 + 50.409 + 105.25 = $405.4 Mil.
Gross Profit was 195.464 + 52.882 + 49.986 + 105.377 = $403.7 Mil.
Total Current Assets was $401.1 Mil.
Total Assets was $1,112.6 Mil.
Property, Plant and Equipment(Net PPE) was $32.0 Mil.
Depreciation, Depletion and Amortization(DDA) was $21.1 Mil.
Selling, General, & Admin. Expense(SGA) was $266.9 Mil.
Total Current Liabilities was $60.6 Mil.
Long-Term Debt & Capital Lease Obligation was $100.3 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) |
| = | (248.656 / 452.871) | / | (245.382 / 405.356) |
| = | 0.549066 | / | 0.605349 |
| | = | 0.907 |
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) |
| = | (403.709 / 405.356) | / | (451.1 / 452.871) |
| = | 0.995937 | / | 0.996089 |
| | = | 0.9998 |
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 - (382.352 + 27.631) / 1113.345) | / | (1 - (401.084 + 32.017) / 1112.611) |
| = | 0.631756 | / | 0.610735 |
| | = | 1.0344 |
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 |
| = | 452.871 | / | 405.356 |
| | = | 1.1172 |
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)) |
| = | (21.108 / (21.108 + 32.017)) | / | (19.916 / (19.916 + 27.631)) |
| = | 0.397327 | / | 0.41887 |
| | = | 0.9486 |
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) |
| = | (260.087 / 452.871) | / | (266.898 / 405.356) |
| = | 0.574307 | / | 0.658429 |
| | = | 0.8722 |
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) |
| = | ((96.087 + 78.538) / 1113.345) | / | ((100.316 + 60.565) / 1112.611) |
| = | 0.156847 | / | 0.144598 |
| | = | 1.0847 |
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 |
| = | (-28.214 - 9.453 | - | -6.692) | / | 1113.345 |
| | = | -0.027822 |
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.
eHealth has a M-score of -2.59 suggests that the company is unlikely to be a manipulator.
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