ABL Bio Beneish M-Score Historical Data
The historical data trend for ABL 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.
ABL Bio Beneish M-Score Chart
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ABL Bio Annual Data
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Trend |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-1.92 |
2.27 |
-4.09 |
5.11 |
-1.65 |
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ABL Bio Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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11.42 |
0.69 |
-3.53 |
-1.65 |
5.15 |
Competitive Comparison of ABL Bio's Beneish M-Score
For the Biotechnology subindustry, ABL 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.
ABL Bio's Beneish M-Score Distribution in the Biotechnology Industry
For the Biotechnology industry and Healthcare sector, ABL Bio's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where ABL Bio's Beneish M-Score falls into.
ABL 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 ABL 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 * 9.1181 | + | 0.528 * 1 | + | 0.404 * 0.1025 | + | 0.892 * 0.3159 | + | 0.115 * 8.563 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 3.54 | + | 4.679 * 0.153477 | - | 0.327 * 1.0492 |
| = | 5.15 |
* 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 (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was ₩248 Mil.
Revenue was 7937.206 + 8004.697 + 8570.734 + 8590.309 = ₩33,103 Mil.
Gross Profit was 7937.206 + 8004.697 + 8570.734 + 8590.309 = ₩33,103 Mil.
Total Current Assets was ₩56,459 Mil.
Total Assets was ₩140,758 Mil.
Property, Plant and Equipment(Net PPE) was ₩77,619 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩2,582 Mil.
Selling, General, & Admin. Expense(SGA) was ₩9,596 Mil.
Total Current Liabilities was ₩32,725 Mil.
Long-Term Debt & Capital Lease Obligation was ₩43,071 Mil.
Net Income was -11971.109 + -12513.49 + -4109.451 + -10358.336 = ₩-38,952 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was -17518.966 + -17343.828 + -11665.697 + -14027.006 = ₩-60,555 Mil.
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Total Receivables was ₩86 Mil.
Revenue was 40381.314 + 9904.013 + 38378.288 + 16139.488 = ₩104,803 Mil.
Gross Profit was 40381.314 + 9904.013 + 38378.288 + 16139.488 = ₩104,803 Mil.
Total Current Assets was ₩102,600 Mil.
Total Assets was ₩202,901 Mil.
Property, Plant and Equipment(Net PPE) was ₩6,391 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩2,433 Mil.
Selling, General, & Admin. Expense(SGA) was ₩8,582 Mil.
Total Current Liabilities was ₩103,724 Mil.
Long-Term Debt & Capital Lease Obligation was ₩410 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) |
| = | (247.793 / 33102.946) | / | (86.025 / 104803.103) |
| = | 0.007486 | / | 0.000821 |
| | = | 9.1181 |
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) |
| = | (104803.103 / 104803.103) | / | (33102.946 / 33102.946) |
| = | 1 | / | 1 |
| | = | 1 |
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 - (56459.415 + 77618.775) / 140758.067) | / | (1 - (102599.621 + 6391.344) / 202901.27) |
| = | 0.047456 | / | 0.462837 |
| | = | 0.1025 |
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 |
| = | 33102.946 | / | 104803.103 |
| | = | 0.3159 |
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)) |
| = | (2432.754 / (2432.754 + 6391.344)) | / | (2582.182 / (2582.182 + 77618.775)) |
| = | 0.275694 | / | 0.032196 |
| | = | 8.563 |
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) |
| = | (9595.69 / 33102.946) | / | (8581.801 / 104803.103) |
| = | 0.289874 | / | 0.081885 |
| | = | 3.54 |
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) |
| = | ((43070.554 + 32724.507) / 140758.067) | / | ((409.916 + 103723.979) / 202901.27) |
| = | 0.538478 | / | 0.513224 |
| | = | 1.0492 |
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 |
| = | (-38952.386 - 0 | - | -60555.497) | / | 140758.067 |
| | = | 0.153477 |
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.
ABL Bio has a M-score of 5.15 signals that the company is likely to be a manipulator.
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