09Women Co Beneish M-Score Historical Data
The historical data trend for 09Women 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.
09Women Co Beneish M-Score Chart
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09Women Co Annual Data
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Trend |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
- |
- |
-1.88 |
-2.17 |
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09Women Co Quarterly Data
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Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-1.88 |
-1.62 |
-2.36 |
-2.22 |
-2.17 |
Competitive Comparison of 09Women Co's Beneish M-Score
For the Internet Retail subindustry, 09Women 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.
09Women Co's Beneish M-Score Distribution in the Retail - Cyclical Industry
For the Retail - Cyclical industry and Consumer Cyclical sector, 09Women Co's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where 09Women Co's Beneish M-Score falls into.
09Women 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 09Women 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 * 1.1777 | + | 0.528 * 0.9905 | + | 0.404 * 1.5498 | + | 0.892 * 0.9033 | + | 0.115 * 0.6676 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.05 | + | 4.679 * -0.002028 | - | 0.327 * 0.792 |
| = | -2.17 |
* 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 (Dec23) TTM: | Last Year (Dec22) TTM: |
Total Receivables was ₩1,897 Mil.
Revenue was 13467.205 + 11637.445 + 16971.866 + 10932.961 = ₩53,009 Mil.
Gross Profit was 6196.956 + 5278.502 + 7788.318 + 4883.879 = ₩24,148 Mil.
Total Current Assets was ₩53,335 Mil.
Total Assets was ₩69,577 Mil.
Property, Plant and Equipment(Net PPE) was ₩10,381 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩871 Mil.
Selling, General, & Admin. Expense(SGA) was ₩8,440 Mil.
Total Current Liabilities was ₩3,134 Mil.
Long-Term Debt & Capital Lease Obligation was ₩251 Mil.
Net Income was 2979.629 + 1935.647 + 2974.652 + 2165.835 = ₩10,056 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 4285.697 + 1949.077 + 3915.335 + 46.751 = ₩10,197 Mil.
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Total Receivables was ₩1,783 Mil.
Revenue was 15332.596 + 14478.086 + 18868.636 + 10007.562 = ₩58,687 Mil.
Gross Profit was 6594.342 + 6549.189 + 8782.754 + 4554.208 = ₩26,480 Mil.
Total Current Assets was ₩47,473 Mil.
Total Assets was ₩63,198 Mil.
Property, Plant and Equipment(Net PPE) was ₩12,290 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩670 Mil.
Selling, General, & Admin. Expense(SGA) was ₩8,899 Mil.
Total Current Liabilities was ₩3,739 Mil.
Long-Term Debt & Capital Lease Obligation was ₩142 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) |
| = | (1896.656 / 53009.477) | / | (1783.035 / 58686.88) |
| = | 0.03578 | / | 0.030382 |
| | = | 1.1777 |
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) |
| = | (26480.493 / 58686.88) | / | (24147.655 / 53009.477) |
| = | 0.451217 | / | 0.455535 |
| | = | 0.9905 |
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 - (53334.762 + 10381.448) / 69576.562) | / | (1 - (47473.058 + 12290.333) / 63198.047) |
| = | 0.084229 | / | 0.054348 |
| | = | 1.5498 |
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 |
| = | 53009.477 | / | 58686.88 |
| | = | 0.9033 |
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)) |
| = | (669.524 / (669.524 + 12290.333)) | / | (870.687 / (870.687 + 10381.448)) |
| = | 0.051661 | / | 0.07738 |
| | = | 0.6676 |
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) |
| = | (8439.531 / 53009.477) | / | (8898.689 / 58686.88) |
| = | 0.159208 | / | 0.15163 |
| | = | 1.05 |
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) |
| = | ((250.53 + 3133.887) / 69576.562) | / | ((141.946 + 3739.389) / 63198.047) |
| = | 0.048643 | / | 0.061415 |
| | = | 0.792 |
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 |
| = | (10055.763 - 0 | - | 10196.86) | / | 69576.562 |
| | = | -0.002028 |
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.
09Women Co has a M-score of -2.17 suggests that the company is unlikely to be a manipulator.
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