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
|
09Women Co Annual Data
|
|
Trend |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
|
- |
- |
- |
-1.88 |
-2.17 |
|
09Women Co Quarterly Data
|
|
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
Get a 7-Day Free Trial
|
|
|
|
|
|
|
|
-1.62 |
-2.36 |
-2.22 |
-2.17 |
-2.36 |
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 * 1.0092 | + | 0.528 * 0.9772 | + | 0.404 * 1.6405 | + | 0.892 * 0.8737 | + | 0.115 * 0.6344 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1011 | + | 4.679 * -0.009036 | - | 0.327 * 0.7568 |
| = | -2.36 |
* 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 ₩1,980 Mil.
Revenue was 10003.976 + 13467.205 + 11637.445 + 16971.866 = ₩52,080 Mil.
Gross Profit was 4704.565 + 6196.956 + 5278.502 + 7788.318 = ₩23,968 Mil.
Total Current Assets was ₩54,801 Mil.
Total Assets was ₩71,125 Mil.
Property, Plant and Equipment(Net PPE) was ₩10,171 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩933 Mil.
Selling, General, & Admin. Expense(SGA) was ₩8,384 Mil.
Total Current Liabilities was ₩5,752 Mil.
Long-Term Debt & Capital Lease Obligation was ₩131 Mil.
Net Income was 1742.321 + 2979.629 + 1935.647 + 2974.652 = ₩9,632 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 124.853 + 4285.697 + 1949.077 + 3915.335 = ₩10,275 Mil.
|
Total Receivables was ₩2,246 Mil.
Revenue was 10932.961 + 15332.596 + 14478.086 + 18868.636 = ₩59,612 Mil.
Gross Profit was 4883.879 + 6594.342 + 6549.189 + 8782.754 = ₩26,810 Mil.
Total Current Assets was ₩49,866 Mil.
Total Assets was ₩65,447 Mil.
Property, Plant and Equipment(Net PPE) was ₩12,131 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩683 Mil.
Selling, General, & Admin. Expense(SGA) was ₩8,715 Mil.
Total Current Liabilities was ₩7,041 Mil.
Long-Term Debt & Capital Lease Obligation was ₩111 Mil.
|
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) |
| = | (1979.941 / 52080.492) | / | (2245.654 / 59612.279) |
| = | 0.038017 | / | 0.037671 |
| | = | 1.0092 |
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) |
| = | (26810.164 / 59612.279) | / | (23968.341 / 52080.492) |
| = | 0.449742 | / | 0.460217 |
| | = | 0.9772 |
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 - (54800.971 + 10170.728) / 71124.717) | / | (1 - (49865.649 + 12130.502) / 65447.397) |
| = | 0.08651 | / | 0.052733 |
| | = | 1.6405 |
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 |
| = | 52080.492 | / | 59612.279 |
| | = | 0.8737 |
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)) |
| = | (683.064 / (683.064 + 12130.502)) | / | (933.01 / (933.01 + 10170.728)) |
| = | 0.053308 | / | 0.084027 |
| | = | 0.6344 |
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) |
| = | (8384.178 / 52080.492) | / | (8715.475 / 59612.279) |
| = | 0.160985 | / | 0.146203 |
| | = | 1.1011 |
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) |
| = | ((131.292 + 5751.623) / 71124.717) | / | ((111.23 + 7041.412) / 65447.397) |
| = | 0.082713 | / | 0.109288 |
| | = | 0.7568 |
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 |
| = | (9632.249 - 0 | - | 10274.962) | / | 71124.717 |
| | = | -0.009036 |
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 -2.36 suggests that the company is unlikely to be a manipulator.
Quick Browse
Personalize
Premium Gurus 
Create New Portfolio
Portfolio Contest
XKRX:366030 has been successfully added to your