Woojin Beneish M-Score Historical Data
The historical data trend for Woojin'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.
Woojin Beneish M-Score Chart
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Woojin Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-1.66 |
-1.41 |
-2.93 |
-2.86 |
-2.41 |
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Woojin 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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-1.85 |
-2.39 |
-1.90 |
-2.41 |
-3.01 |
Competitive Comparison of Woojin's Beneish M-Score
For the Scientific & Technical Instruments subindustry, Woojin'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.
Woojin's Beneish M-Score Distribution in the Hardware Industry
For the Hardware industry and Technology sector, Woojin's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Woojin's Beneish M-Score falls into.
Woojin 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 Woojin 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 * 0.8586 | + | 0.528 * 0.9403 | + | 0.404 * 0.6801 | + | 0.892 * 1.0175 | + | 0.115 * 1.1511 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1291 | + | 4.679 * -0.049065 | - | 0.327 * 1.0629 |
| = | -3.01 |
* 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 ₩18,427 Mil.
Revenue was 35766.702 + 36143.745 + 28518.451 + 32649.844 = ₩133,079 Mil.
Gross Profit was 12955.188 + 10839.314 + 8832.726 + 12796.188 = ₩45,423 Mil.
Total Current Assets was ₩112,012 Mil.
Total Assets was ₩247,961 Mil.
Property, Plant and Equipment(Net PPE) was ₩111,817 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩3,001 Mil.
Selling, General, & Admin. Expense(SGA) was ₩7,456 Mil.
Total Current Liabilities was ₩24,911 Mil.
Long-Term Debt & Capital Lease Obligation was ₩1,326 Mil.
Net Income was 5041.579 + -684.109 + 2522.591 + 4594.271 = ₩11,474 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 3963.27 + 11836.719 + -1361.533 + 9202.049 = ₩23,641 Mil.
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Total Receivables was ₩21,094 Mil.
Revenue was 31747.281 + 34461.407 + 33087.772 + 31497.266 = ₩130,794 Mil.
Gross Profit was 10742.634 + 10895.377 + 10950.755 + 9390.811 = ₩41,980 Mil.
Total Current Assets was ₩78,757 Mil.
Total Assets was ₩210,378 Mil.
Property, Plant and Equipment(Net PPE) was ₩101,518 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩3,149 Mil.
Selling, General, & Admin. Expense(SGA) was ₩6,490 Mil.
Total Current Liabilities was ₩17,222 Mil.
Long-Term Debt & Capital Lease Obligation was ₩3,720 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) |
| = | (18426.612 / 133078.742) | / | (21093.945 / 130793.726) |
| = | 0.138464 | / | 0.161276 |
| | = | 0.8586 |
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) |
| = | (41979.577 / 130793.726) | / | (45423.416 / 133078.742) |
| = | 0.32096 | / | 0.341327 |
| | = | 0.9403 |
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 - (112011.83 + 111817.38) / 247960.628) | / | (1 - (78757.133 + 101517.788) / 210378.221) |
| = | 0.09732 | / | 0.143091 |
| | = | 0.6801 |
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 |
| = | 133078.742 | / | 130793.726 |
| | = | 1.0175 |
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)) |
| = | (3148.781 / (3148.781 + 101517.788)) | / | (3000.862 / (3000.862 + 111817.38)) |
| = | 0.030084 | / | 0.026136 |
| | = | 1.1511 |
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) |
| = | (7455.929 / 133078.742) | / | (6490.178 / 130793.726) |
| = | 0.056026 | / | 0.049621 |
| | = | 1.1291 |
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) |
| = | ((1325.51 + 24910.532) / 247960.628) | / | ((3719.619 + 17222.014) / 210378.221) |
| = | 0.105807 | / | 0.099543 |
| | = | 1.0629 |
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 |
| = | (11474.332 - 0 | - | 23640.505) | / | 247960.628 |
| | = | -0.049065 |
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.
Woojin has a M-score of -3.01 suggests that the company is unlikely to be a manipulator.
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