Beautyskin Co Beneish M-Score Historical Data
The historical data trend for Beautyskin 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.
Beautyskin Co Beneish M-Score Chart
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Beautyskin Co Annual Data
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Trend |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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- |
- |
- |
0.03 |
-3.55 |
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Beautyskin Co Quarterly Data
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Dec18 |
Dec19 |
Dec20 |
Dec21 |
Mar22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
| Beneish M-Score |
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0.03 |
-0.68 |
- |
-2.40 |
-3.55 |
Competitive Comparison of Beautyskin Co's Beneish M-Score
For the Household & Personal Products subindustry, Beautyskin 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.
Beautyskin Co's Beneish M-Score Distribution in the Consumer Packaged Goods Industry
For the Consumer Packaged Goods industry and Consumer Defensive sector, Beautyskin Co's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Beautyskin Co's Beneish M-Score falls into.
Beautyskin 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 Beautyskin 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 * 0.7152 | + | 0.528 * 0.8692 | + | 0.404 * 1.0403 | + | 0.892 * 0.9996 | + | 0.115 * 1.2071 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8919 | + | 4.679 * -0.168109 | - | 0.327 * 1.0268 |
| = | -3.55 |
* 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 ₩17,096 Mil.
Revenue was 16114.671 + 18185.239 + 26897.52 + 19673.899 = ₩80,871 Mil.
Gross Profit was -295.255 + 1593.883 + 4445.918 + 2521.674 = ₩8,266 Mil.
Total Current Assets was ₩40,485 Mil.
Total Assets was ₩82,994 Mil.
Property, Plant and Equipment(Net PPE) was ₩25,929 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩1,754 Mil.
Selling, General, & Admin. Expense(SGA) was ₩5,393 Mil.
Total Current Liabilities was ₩38,751 Mil.
Long-Term Debt & Capital Lease Obligation was ₩5,991 Mil.
Net Income was -5785.118 + -1324.707 + 671.261 + 1376.229 = ₩-5,062 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 1894.197 + 543.11 + -334.812 + 6787.269 = ₩8,890 Mil.
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Total Receivables was ₩23,913 Mil.
Revenue was 23071.673 + 20004.804 + 21730.879 + 16096.155 = ₩80,904 Mil.
Gross Profit was -1686.982 + 2721.628 + 3240.054 + 2913.188 = ₩7,188 Mil.
Total Current Assets was ₩38,116 Mil.
Total Assets was ₩74,235 Mil.
Property, Plant and Equipment(Net PPE) was ₩21,863 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩1,810 Mil.
Selling, General, & Admin. Expense(SGA) was ₩6,049 Mil.
Total Current Liabilities was ₩37,228 Mil.
Long-Term Debt & Capital Lease Obligation was ₩1,749 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) |
| = | (17095.983 / 80871.329) | / | (23912.64 / 80903.511) |
| = | 0.211397 | / | 0.29557 |
| | = | 0.7152 |
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) |
| = | (7187.888 / 80903.511) | / | (8266.22 / 80871.329) |
| = | 0.088845 | / | 0.102214 |
| | = | 0.8692 |
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 - (40484.792 + 25928.85) / 82994.422) | / | (1 - (38115.636 + 21863) / 74235.175) |
| = | 0.199782 | / | 0.192046 |
| | = | 1.0403 |
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 |
| = | 80871.329 | / | 80903.511 |
| | = | 0.9996 |
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)) |
| = | (1810.316 / (1810.316 + 21863)) | / | (1753.763 / (1753.763 + 25928.85)) |
| = | 0.076471 | / | 0.063353 |
| | = | 1.2071 |
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) |
| = | (5392.748 / 80871.329) | / | (6048.879 / 80903.511) |
| = | 0.066683 | / | 0.074767 |
| | = | 0.8919 |
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) |
| = | ((5991.357 + 38751.491) / 82994.422) | / | ((1748.761 + 37227.911) / 74235.175) |
| = | 0.539107 | / | 0.525043 |
| | = | 1.0268 |
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 |
| = | (-5062.335 - 0 | - | 8889.764) | / | 82994.422 |
| | = | -0.168109 |
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.
Beautyskin Co has a M-score of -3.55 suggests that the company is unlikely to be a manipulator.
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