Easy Bio Beneish M-Score Historical Data
The historical data trend for Easy Bio'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.
Easy Bio Beneish M-Score Chart
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Easy Bio Annual Data
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Trend |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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- |
- |
-1.40 |
-2.29 |
- |
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Easy Bio Quarterly Data
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Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
| Beneish M-Score |
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-2.29 |
-2.25 |
-1.40 |
-1.72 |
- |
Competitive Comparison of Easy Bio's Beneish M-Score
For the Biotechnology subindustry, Easy Bio'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.
Easy Bio's Beneish M-Score Distribution in the Biotechnology Industry
For the Biotechnology industry and Healthcare sector, Easy Bio's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Easy Bio's Beneish M-Score falls into.
Easy Bio 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 Easy Bio 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 * 0.7035 | + | 0.528 * 1.2275 | + | 0.404 * 2.0203 | + | 0.892 * 2.3239 | + | 0.115 * 0.9308 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.6217 | + | 4.679 * -0.017085 | - | 0.327 * 1.2379 |
| = | -1.14 |
* 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 (Dec24) TTM: | Last Year (Dec23) TTM: |
Total Receivables was ₩99,966 Mil.
Revenue was 117623.845 + 106421.589 + 100882.878 + 59402.599 = ₩384,331 Mil.
Gross Profit was 22682.429 + 29437.734 + 27890.601 + 18467.645 = ₩98,478 Mil.
Total Current Assets was ₩219,027 Mil.
Total Assets was ₩360,012 Mil.
Property, Plant and Equipment(Net PPE) was ₩64,558 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩7,505 Mil.
Selling, General, & Admin. Expense(SGA) was ₩22,399 Mil.
Total Current Liabilities was ₩127,758 Mil.
Long-Term Debt & Capital Lease Obligation was ₩137,431 Mil.
Net Income was 4356.477 + 6217.265 + 4349.661 + 4680.981 = ₩19,604 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 14495.26 + 5302.522 + 962.764 + 4994.682 = ₩25,755 Mil.
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Total Receivables was ₩61,145 Mil.
Revenue was 42581.181 + 42665.277 + 40551.574 + 39587.059 = ₩165,385 Mil.
Gross Profit was 13561.07 + 13771.395 + 12959.125 + 11725.998 = ₩52,018 Mil.
Total Current Assets was ₩119,571 Mil.
Total Assets was ₩172,042 Mil.
Property, Plant and Equipment(Net PPE) was ₩34,393 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩3,692 Mil.
Selling, General, & Admin. Expense(SGA) was ₩15,504 Mil.
Total Current Liabilities was ₩71,919 Mil.
Long-Term Debt & Capital Lease Obligation was ₩30,454 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) |
| = | (99966.211 / 384330.911) | / | (61145.13 / 165385.091) |
| = | 0.260105 | / | 0.369714 |
| | = | 0.7035 |
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) |
| = | (52017.588 / 165385.091) | / | (98478.409 / 384330.911) |
| = | 0.314524 | / | 0.256233 |
| | = | 1.2275 |
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 - (219027.424 + 64557.983) / 360011.558) | / | (1 - (119570.925 + 34393.442) / 172041.553) |
| = | 0.212288 | / | 0.105075 |
| | = | 2.0203 |
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 |
| = | 384330.911 | / | 165385.091 |
| | = | 2.3239 |
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)) |
| = | (3691.923 / (3691.923 + 34393.442)) | / | (7504.97 / (7504.97 + 64557.983)) |
| = | 0.096938 | / | 0.104145 |
| | = | 0.9308 |
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) |
| = | (22399.299 / 384330.911) | / | (15504.02 / 165385.091) |
| = | 0.058281 | / | 0.093745 |
| | = | 0.6217 |
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) |
| = | ((137430.698 + 127757.917) / 360011.558) | / | ((30453.615 + 71918.845) / 172041.553) |
| = | 0.736611 | / | 0.595045 |
| | = | 1.2379 |
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 |
| = | (19604.384 - 0 | - | 25755.228) | / | 360011.558 |
| | = | -0.017085 |
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.
Easy Bio has a M-score of -1.14 signals that the company is likely to be a manipulator.
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