Coreline Soft Co Beneish M-Score Historical Data
The historical data trend for Coreline Soft Co'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.
Coreline Soft Co Beneish M-Score Chart
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Coreline Soft Co Annual Data
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Trend |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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- |
- |
- |
- |
2.89 |
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Coreline Soft Co Quarterly Data
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Dec20 |
Dec21 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
| Beneish M-Score |
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- |
- |
- |
2.55 |
2.89 |
Competitive Comparison of Coreline Soft Co's Beneish M-Score
For the Diagnostics & Research subindustry, Coreline Soft Co'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.
Coreline Soft Co's Beneish M-Score Distribution in the Medical Diagnostics & Research Industry
For the Medical Diagnostics & Research industry and Healthcare sector, Coreline Soft Co's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Coreline Soft Co's Beneish M-Score falls into.
Coreline Soft Co 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 Coreline Soft Co 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 * 1.7685 | + | 0.528 * 1 | + | 0.404 * 15.3014 | + | 0.892 * 0.9582 | + | 0.115 * 1.7637 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9878 | + | 4.679 * -0.134629 | - | 0.327 * 2.637 |
| = | 2.89 |
* 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 ₩1,452 Mil.
Revenue was 911.781 + 845.882 + 1458.85 + 712.669 = ₩3,929 Mil.
Gross Profit was 911.781 + 845.882 + 1458.85 + 712.669 = ₩3,929 Mil.
Total Current Assets was ₩15,230 Mil.
Total Assets was ₩24,665 Mil.
Property, Plant and Equipment(Net PPE) was ₩2,419 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩891 Mil.
Selling, General, & Admin. Expense(SGA) was ₩6,019 Mil.
Total Current Liabilities was ₩2,650 Mil.
Long-Term Debt & Capital Lease Obligation was ₩12,231 Mil.
Net Income was -4374.064 + -3634.526 + -3069.951 + -3059.361 = ₩-14,138 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was -2527.587 + -2467.289 + -2730.168 + -3092.246 = ₩-10,817 Mil.
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Total Receivables was ₩857 Mil.
Revenue was 1256.117 + 996.513 + 1051.916 + 796.086 = ₩4,101 Mil.
Gross Profit was 1256.117 + 996.513 + 1051.916 + 796.086 = ₩4,101 Mil.
Total Current Assets was ₩14,712 Mil.
Total Assets was ₩15,862 Mil.
Property, Plant and Equipment(Net PPE) was ₩855 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩773 Mil.
Selling, General, & Admin. Expense(SGA) was ₩6,359 Mil.
Total Current Liabilities was ₩2,493 Mil.
Long-Term Debt & Capital Lease Obligation was ₩1,136 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) |
| = | (1451.81 / 3929.182) | / | (856.742 / 4100.632) |
| = | 0.369494 | / | 0.208929 |
| | = | 1.7685 |
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) |
| = | (4100.632 / 4100.632) | / | (3929.182 / 3929.182) |
| = | 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 - (15230.16 + 2418.7) / 24664.847) | / | (1 - (14711.785 + 855.278) / 15861.941) |
| = | 0.284453 | / | 0.01859 |
| | = | 15.3014 |
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 |
| = | 3929.182 | / | 4100.632 |
| | = | 0.9582 |
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)) |
| = | (772.802 / (772.802 + 855.278)) | / | (890.679 / (890.679 + 2418.7)) |
| = | 0.474671 | / | 0.269138 |
| | = | 1.7637 |
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) |
| = | (6018.671 / 3929.182) | / | (6359.106 / 4100.632) |
| = | 1.531787 | / | 1.550762 |
| | = | 0.9878 |
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) |
| = | ((12230.696 + 2649.798) / 24664.847) | / | ((1135.9 + 2493.108) / 15861.941) |
| = | 0.603308 | / | 0.228787 |
| | = | 2.637 |
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 |
| = | (-14137.902 - 0 | - | -10817.29) | / | 24664.847 |
| | = | -0.134629 |
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.
Coreline Soft Co has a M-score of 2.89 signals that the company is likely to be a manipulator.
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