Repligen Beneish M-Score Historical Data
The historical data trend for Repligen'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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Repligen Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.53 |
-1.94 |
-1.73 |
-2.50 |
-2.57 |
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Repligen 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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-2.50 |
-2.42 |
-2.50 |
-2.65 |
-2.57 |
Competitive Comparison
For the Medical Instruments & Supplies subindustry, Repligen'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.
Repligen Beneish M-Score Distribution
For the Medical Devices & Instruments industry and Healthcare sector, Repligen's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Repligen's Beneish M-Score falls into.
Repligen 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 Repligen 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 * 1.3403 | + | 0.528 * 1.275 | + | 0.404 * 1.0264 | + | 0.892 * 0.7969 | + | 0.115 * 0.7986 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.2681 | + | 4.679 * -0.043369 | - | 0.327 * 1.3266 |
| = | -2.57 |
* 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 $124.2 Mil.
Revenue was 155.743 + 141.192 + 159.169 + 182.66 = $638.8 Mil.
Gross Profit was 67.607 + 36.558 + 79.862 + 100.815 = $284.8 Mil.
Total Current Assets was $1,111.0 Mil.
Total Assets was $2,824.4 Mil.
Property, Plant and Equipment(Net PPE) was $323.0 Mil.
Depreciation, Depletion and Amortization(DDA) was $68.1 Mil.
Selling, General, & Admin. Expense(SGA) was $218.1 Mil.
Total Current Liabilities was $158.2 Mil.
Long-Term Debt & Capital Lease Obligation was $636.7 Mil.
Net Income was -25.488 + 18.172 + 20.064 + 28.829 = $41.6 Mil.
Non Operating Income was -0.727 + 41.849 + 4.701 + 4.328 = $50.2 Mil.
Cash Flow from Operations was 29.065 + 39.231 + 34.468 + 11.154 = $113.9 Mil.
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Total Receivables was $116.2 Mil.
Revenue was 186.762 + 200.741 + 207.633 + 206.4 = $801.5 Mil.
Gross Profit was 96.062 + 114.227 + 121.373 + 124.044 = $455.7 Mil.
Total Current Assets was $998.1 Mil.
Total Assets was $2,524.7 Mil.
Property, Plant and Equipment(Net PPE) was $315.7 Mil.
Depreciation, Depletion and Amortization(DDA) was $51.0 Mil.
Selling, General, & Admin. Expense(SGA) was $215.8 Mil.
Total Current Liabilities was $404.2 Mil.
Long-Term Debt & Capital Lease Obligation was $131.4 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) |
| = | (124.161 / 638.764) | / | (116.247 / 801.536) |
| = | 0.194377 | / | 0.14503 |
| | = | 1.3403 |
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) |
| = | (455.706 / 801.536) | / | (284.842 / 638.764) |
| = | 0.568541 | / | 0.445927 |
| | = | 1.275 |
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 - (1111.043 + 322.955) / 2824.411) | / | (1 - (998.118 + 315.696) / 2524.658) |
| = | 0.492284 | / | 0.479607 |
| | = | 1.0264 |
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 |
| = | 638.764 | / | 801.536 |
| | = | 0.7969 |
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)) |
| = | (50.985 / (50.985 + 315.696)) | / | (68.085 / (68.085 + 322.955)) |
| = | 0.139045 | / | 0.174113 |
| | = | 0.7986 |
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) |
| = | (218.113 / 638.764) | / | (215.829 / 801.536) |
| = | 0.341461 | / | 0.269269 |
| | = | 1.2681 |
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) |
| = | ((636.721 + 158.162) / 2824.411) | / | ((131.389 + 404.196) / 2524.658) |
| = | 0.281433 | / | 0.212142 |
| | = | 1.3266 |
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 |
| = | (41.577 - 50.151 | - | 113.918) | / | 2824.411 |
| | = | -0.043369 |
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.
Repligen has a M-score of -2.57 suggests that the company is unlikely to be a manipulator.
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