AngioLab Beneish M-Score Historical Data
The historical data trend for AngioLab'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.
AngioLab Beneish M-Score Chart
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AngioLab Annual Data
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Trend |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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3.74 |
-4.26 |
-2.87 |
1.84 |
0.60 |
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AngioLab Semi-Annual Data
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Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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3.74 |
-4.26 |
-2.87 |
1.84 |
0.60 |
Competitive Comparison of AngioLab's Beneish M-Score
For the Biotechnology subindustry, AngioLab'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.
AngioLab's Beneish M-Score Distribution in the Biotechnology Industry
For the Biotechnology industry and Healthcare sector, AngioLab's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where AngioLab's Beneish M-Score falls into.
AngioLab 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 AngioLab 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 * 0.1005 | + | 0.528 * 0.2896 | + | 0.404 * 1.3566 | + | 0.892 * 4.1165 | + | 0.115 * 0.8998 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.176 | + | 4.679 * 0.258406 | - | 0.327 * 0.9338 |
| = | 0.60 |
* 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 ₩64 Mil.
Revenue was ₩2,044 Mil.
Gross Profit was ₩1,434 Mil.
Total Current Assets was ₩1,728 Mil.
Total Assets was ₩2,280 Mil.
Property, Plant and Equipment(Net PPE) was ₩127 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩100 Mil.
Selling, General, & Admin. Expense(SGA) was ₩211 Mil.
Total Current Liabilities was ₩999 Mil.
Long-Term Debt & Capital Lease Obligation was ₩26 Mil.
Net Income was ₩-794 Mil.
Gross Profit was ₩0 Mil.
Cash Flow from Operations was ₩-1,383 Mil.
|
Total Receivables was ₩156 Mil.
Revenue was ₩497 Mil.
Gross Profit was ₩101 Mil.
Total Current Assets was ₩3,206 Mil.
Total Assets was ₩3,919 Mil.
Property, Plant and Equipment(Net PPE) was ₩175 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩114 Mil.
Selling, General, & Admin. Expense(SGA) was ₩291 Mil.
Total Current Liabilities was ₩1,842 Mil.
Long-Term Debt & Capital Lease Obligation was ₩44 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) |
| = | (64.497 / 2044.464) | / | (155.963 / 496.646) |
| = | 0.031547 | / | 0.314033 |
| | = | 0.1005 |
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) |
| = | (100.926 / 496.646) | / | (1434.473 / 2044.464) |
| = | 0.203215 | / | 0.701638 |
| | = | 0.2896 |
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 - (1728.32 + 126.894) / 2279.662) | / | (1 - (3205.956 + 174.77) / 3918.531) |
| = | 0.186189 | / | 0.137247 |
| | = | 1.3566 |
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 |
| = | 2044.464 | / | 496.646 |
| | = | 4.1165 |
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)) |
| = | (114.488 / (114.488 + 174.77)) | / | (99.652 / (99.652 + 126.894)) |
| = | 0.395799 | / | 0.439875 |
| | = | 0.8998 |
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) |
| = | (210.518 / 2044.464) | / | (290.589 / 496.646) |
| = | 0.10297 | / | 0.585103 |
| | = | 0.176 |
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) |
| = | ((26.165 + 998.543) / 2279.662) | / | ((43.969 + 1842.377) / 3918.531) |
| = | 0.4495 | / | 0.481391 |
| | = | 0.9338 |
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 |
| = | (-793.963 - 0 | - | -1383.041) | / | 2279.662 |
| | = | 0.258406 |
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.
AngioLab has a M-score of 0.60 signals that the company is likely to be a manipulator.
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