Sunjin Beauty Science Co Beneish M-Score Historical Data
The historical data trend for Sunjin Beauty Science 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.
Sunjin Beauty Science Co Beneish M-Score Chart
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Sunjin Beauty Science Co Annual Data
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Trend |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
- |
- |
-1.06 |
-2.63 |
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Sunjin Beauty Science Co Quarterly Data
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Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-1.92 |
-1.93 |
-1.80 |
-2.63 |
-2.22 |
Competitive Comparison of Sunjin Beauty Science Co's Beneish M-Score
For the Specialty Chemicals subindustry, Sunjin Beauty Science 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.
Sunjin Beauty Science Co's Beneish M-Score Distribution in the Chemicals Industry
For the Chemicals industry and Basic Materials sector, Sunjin Beauty Science Co's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Sunjin Beauty Science Co's Beneish M-Score falls into.
Sunjin Beauty Science 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 Sunjin Beauty Science 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 * 1.056 | + | 0.528 * 0.9242 | + | 0.404 * 1.2216 | + | 0.892 * 1.067 | + | 0.115 * 0.9481 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9112 | + | 4.679 * 0.012013 | - | 0.327 * 0.8874 |
| = | -2.22 |
* 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 ₩15,851 Mil.
Revenue was 20793.872 + 17908.411 + 15278.876 + 19042.482 = ₩73,024 Mil.
Gross Profit was 7516.171 + 5892.107 + 5408.708 + 6277.931 = ₩25,095 Mil.
Total Current Assets was ₩43,321 Mil.
Total Assets was ₩130,119 Mil.
Property, Plant and Equipment(Net PPE) was ₩81,934 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩5,620 Mil.
Selling, General, & Admin. Expense(SGA) was ₩10,826 Mil.
Total Current Liabilities was ₩29,066 Mil.
Long-Term Debt & Capital Lease Obligation was ₩23,205 Mil.
Net Income was 3253.331 + 1132.783 + 161.354 + 1615.21 = ₩6,163 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 4390.552 + 219.313 + -183.717 + 173.459 = ₩4,600 Mil.
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Total Receivables was ₩14,068 Mil.
Revenue was 20392.591 + 17634.775 + 14400.645 + 16010.366 = ₩68,438 Mil.
Gross Profit was 6861.926 + 5336.492 + 4659.927 + 4877.317 = ₩21,736 Mil.
Total Current Assets was ₩49,631 Mil.
Total Assets was ₩131,153 Mil.
Property, Plant and Equipment(Net PPE) was ₩77,509 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩5,023 Mil.
Selling, General, & Admin. Expense(SGA) was ₩11,135 Mil.
Total Current Liabilities was ₩31,255 Mil.
Long-Term Debt & Capital Lease Obligation was ₩28,116 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) |
| = | (15851.208 / 73023.641) | / | (14068.34 / 68438.377) |
| = | 0.21707 | / | 0.205562 |
| | = | 1.056 |
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) |
| = | (21735.662 / 68438.377) | / | (25094.917 / 73023.641) |
| = | 0.317595 | / | 0.343655 |
| | = | 0.9242 |
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 - (43320.942 + 81933.82) / 130118.633) | / | (1 - (49631.244 + 77508.524) / 131152.753) |
| = | 0.03738 | / | 0.030598 |
| | = | 1.2216 |
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 |
| = | 73023.641 | / | 68438.377 |
| | = | 1.067 |
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)) |
| = | (5023.341 / (5023.341 + 77508.524)) | / | (5620.456 / (5620.456 + 81933.82)) |
| = | 0.060865 | / | 0.064194 |
| | = | 0.9481 |
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) |
| = | (10825.882 / 73023.641) | / | (11135.479 / 68438.377) |
| = | 0.148252 | / | 0.162708 |
| | = | 0.9112 |
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) |
| = | ((23204.9 + 29066.344) / 130118.633) | / | ((28115.66 + 31255.24) / 131152.753) |
| = | 0.40172 | / | 0.452685 |
| | = | 0.8874 |
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 |
| = | (6162.678 - 0 | - | 4599.607) | / | 130118.633 |
| | = | 0.012013 |
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.
Sunjin Beauty Science Co has a M-score of -2.22 suggests that the company is unlikely to be a manipulator.
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