CTC Bio Beneish M-Score Historical Data
The historical data trend for CTC 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.
CTC Bio Beneish M-Score Chart
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CTC Bio Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.73 |
-2.98 |
-2.92 |
-3.07 |
-3.31 |
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CTC Bio Quarterly Data
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Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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-3.26 |
-3.31 |
-3.14 |
-3.03 |
-3.24 |
Competitive Comparison of CTC Bio's Beneish M-Score
For the Biotechnology subindustry, CTC 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.
CTC Bio's Beneish M-Score Distribution in the Biotechnology Industry
For the Biotechnology industry and Healthcare sector, CTC Bio's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where CTC Bio's Beneish M-Score falls into.
CTC 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 CTC 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 * 0.911 | + | 0.528 * 0.9225 | + | 0.404 * 0.9784 | + | 0.892 * 1.0053 | + | 0.115 * 0.9911 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1677 | + | 4.679 * -0.123365 | - | 0.327 * 1.0818 |
| = | -3.24 |
* 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 (Sep24) TTM: | Last Year (Sep23) TTM: |
Total Receivables was ₩20,743 Mil.
Revenue was 35791.975 + 34817.4 + 33192.978 + 35146.963 = ₩138,949 Mil.
Gross Profit was 11008.145 + 13148.67 + 12393.026 + 10466.715 = ₩47,017 Mil.
Total Current Assets was ₩74,147 Mil.
Total Assets was ₩155,021 Mil.
Property, Plant and Equipment(Net PPE) was ₩62,197 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩5,537 Mil.
Selling, General, & Admin. Expense(SGA) was ₩32,676 Mil.
Total Current Liabilities was ₩68,456 Mil.
Long-Term Debt & Capital Lease Obligation was ₩4,286 Mil.
Net Income was -3183.539 + -2254.76 + -284.013 + -11071.451 = ₩-16,794 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 3409.311 + 1276.661 + -2596.036 + 240.455 = ₩2,330 Mil.
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Total Receivables was ₩22,650 Mil.
Revenue was 31188.779 + 36296.031 + 35246.263 + 35483.11 = ₩138,214 Mil.
Gross Profit was 9530.573 + 12843.522 + 10225.669 + 10541.782 = ₩43,142 Mil.
Total Current Assets was ₩85,106 Mil.
Total Assets was ₩178,443 Mil.
Property, Plant and Equipment(Net PPE) was ₩71,363 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩6,291 Mil.
Selling, General, & Admin. Expense(SGA) was ₩27,837 Mil.
Total Current Liabilities was ₩72,591 Mil.
Long-Term Debt & Capital Lease Obligation was ₩4,808 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) |
| = | (20743.139 / 138949.316) | / | (22649.631 / 138214.183) |
| = | 0.149286 | / | 0.163873 |
| | = | 0.911 |
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) |
| = | (43141.546 / 138214.183) | / | (47016.556 / 138949.316) |
| = | 0.312135 | / | 0.338372 |
| | = | 0.9225 |
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 - (74146.833 + 62197.224) / 155020.743) | / | (1 - (85105.878 + 71362.978) / 178443.256) |
| = | 0.120479 | / | 0.123145 |
| | = | 0.9784 |
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 |
| = | 138949.316 | / | 138214.183 |
| | = | 1.0053 |
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)) |
| = | (6291.427 / (6291.427 + 71362.978)) | / | (5536.921 / (5536.921 + 62197.224)) |
| = | 0.081018 | / | 0.081745 |
| | = | 0.9911 |
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) |
| = | (32676.485 / 138949.316) | / | (27836.542 / 138214.183) |
| = | 0.235168 | / | 0.201401 |
| | = | 1.1677 |
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) |
| = | ((4286.476 + 68456.239) / 155020.743) | / | ((4807.675 + 72591.364) / 178443.256) |
| = | 0.469245 | / | 0.433746 |
| | = | 1.0818 |
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 |
| = | (-16793.763 - 0 | - | 2330.391) | / | 155020.743 |
| | = | -0.123365 |
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.
CTC Bio has a M-score of -3.24 suggests that the company is unlikely to be a manipulator.
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