Seowon Co Beneish M-Score Historical Data
The historical data trend for Seowon 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.
Seowon Co Beneish M-Score Chart
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Seowon Co Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.27 |
-2.46 |
-2.05 |
-1.99 |
-2.46 |
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Seowon Co 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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-2.19 |
-2.79 |
-2.37 |
-2.46 |
5.56 |
Competitive Comparison of Seowon Co's Beneish M-Score
For the Metal Fabrication subindustry, Seowon 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.
Seowon Co's Beneish M-Score Distribution in the Industrial Products Industry
For the Industrial Products industry and Industrials sector, Seowon Co's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Seowon Co's Beneish M-Score falls into.
Seowon 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 Seowon 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 * 9.7665 | + | 0.528 * 0.8889 | + | 0.404 * 0.0849 | + | 0.892 * 0.9074 | + | 0.115 * 5.3196 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8788 | + | 4.679 * 0.021067 | - | 0.327 * 1.3885 |
| = | 5.56 |
* 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 ₩246,340 Mil.
Revenue was 59580.99 + 60087.924 + 54643.799 + 58159.642 = ₩232,472 Mil.
Gross Profit was 2233.337 + 3557.34 + 2356.52 + 1260.4 = ₩9,408 Mil.
Total Current Assets was ₩541,325 Mil.
Total Assets was ₩913,329 Mil.
Property, Plant and Equipment(Net PPE) was ₩340,688 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩1,772 Mil.
Selling, General, & Admin. Expense(SGA) was ₩3,208 Mil.
Total Current Liabilities was ₩520,351 Mil.
Long-Term Debt & Capital Lease Obligation was ₩89,152 Mil.
Net Income was 28280.577 + -226.243 + -4284.713 + -882.183 = ₩22,887 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was -1426.074 + 16083.828 + -16611.853 + 5600.119 = ₩3,646 Mil.
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Total Receivables was ₩27,798 Mil.
Revenue was 60287.903 + 59424.559 + 58384.429 + 78104.317 = ₩256,201 Mil.
Gross Profit was 2166.675 + 5267.038 + -253.395 + 2035.631 = ₩9,216 Mil.
Total Current Assets was ₩93,479 Mil.
Total Assets was ₩263,179 Mil.
Property, Plant and Equipment(Net PPE) was ₩63,458 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩1,796 Mil.
Selling, General, & Admin. Expense(SGA) was ₩4,023 Mil.
Total Current Liabilities was ₩101,333 Mil.
Long-Term Debt & Capital Lease Obligation was ₩25,157 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) |
| = | (246339.949 / 232472.355) | / | (27797.507 / 256201.208) |
| = | 1.059653 | / | 0.108499 |
| | = | 9.7665 |
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) |
| = | (9215.949 / 256201.208) | / | (9407.597 / 232472.355) |
| = | 0.035972 | / | 0.040468 |
| | = | 0.8889 |
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 - (541325.351 + 340687.51) / 913329.065) | / | (1 - (93478.564 + 63458.258) / 263179.19) |
| = | 0.034288 | / | 0.403688 |
| | = | 0.0849 |
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 |
| = | 232472.355 | / | 256201.208 |
| | = | 0.9074 |
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)) |
| = | (1796.385 / (1796.385 + 63458.258)) | / | (1772.398 / (1772.398 + 340687.51)) |
| = | 0.027529 | / | 0.005175 |
| | = | 5.3196 |
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) |
| = | (3208.029 / 232472.355) | / | (4023.266 / 256201.208) |
| = | 0.0138 | / | 0.015704 |
| | = | 0.8788 |
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) |
| = | ((89152.496 + 520351.327) / 913329.065) | / | ((25156.735 + 101332.804) / 263179.19) |
| = | 0.667343 | / | 0.480621 |
| | = | 1.3885 |
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 |
| = | (22887.438 - 0 | - | 3646.02) | / | 913329.065 |
| | = | 0.021067 |
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.
Seowon Co has a M-score of 5.56 signals that the company is likely to be a manipulator.
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