YES24 Co Beneish M-Score Historical Data
The historical data trend for YES24 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.
YES24 Co Beneish M-Score Chart
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YES24 Co Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.28 |
-2.03 |
-2.50 |
-2.81 |
-2.70 |
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YES24 Co 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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-2.64 |
-2.48 |
-2.69 |
-2.70 |
-2.92 |
Competitive Comparison of YES24 Co's Beneish M-Score
For the Internet Retail subindustry, YES24 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.
YES24 Co's Beneish M-Score Distribution in the Retail - Cyclical Industry
For the Retail - Cyclical industry and Consumer Cyclical sector, YES24 Co's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where YES24 Co's Beneish M-Score falls into.
YES24 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 YES24 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 * 0.8738 | + | 0.528 * 0.9703 | + | 0.404 * 0.9041 | + | 0.892 * 0.9819 | + | 0.115 * 1.3564 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0944 | + | 4.679 * -0.063222 | - | 0.327 * 0.936 |
| = | -2.92 |
* 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 ₩34,757 Mil.
Revenue was 172860.854 + 164204.685 + 158083.322 + 155377.488 = ₩650,526 Mil.
Gross Profit was 32805.118 + 35984.056 + 31644.081 + 35686.038 = ₩136,119 Mil.
Total Current Assets was ₩103,552 Mil.
Total Assets was ₩441,739 Mil.
Property, Plant and Equipment(Net PPE) was ₩108,353 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩15,096 Mil.
Selling, General, & Admin. Expense(SGA) was ₩82,073 Mil.
Total Current Liabilities was ₩193,547 Mil.
Long-Term Debt & Capital Lease Obligation was ₩9,628 Mil.
Net Income was -197.385 + -4511.873 + -476.394 + -374.645 = ₩-5,560 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 7254.192 + 14786.139 + 1067.19 + -740.087 = ₩22,367 Mil.
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Total Receivables was ₩40,514 Mil.
Revenue was 180178.493 + 166650.417 + 158830.511 + 156883.224 = ₩662,543 Mil.
Gross Profit was 34561.739 + 36790.975 + 31403.058 + 31758.001 = ₩134,514 Mil.
Total Current Assets was ₩95,709 Mil.
Total Assets was ₩386,071 Mil.
Property, Plant and Equipment(Net PPE) was ₩68,178 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩13,557 Mil.
Selling, General, & Admin. Expense(SGA) was ₩76,380 Mil.
Total Current Liabilities was ₩185,885 Mil.
Long-Term Debt & Capital Lease Obligation was ₩3,821 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) |
| = | (34756.974 / 650526.349) | / | (40513.503 / 662542.645) |
| = | 0.053429 | / | 0.061149 |
| | = | 0.8738 |
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) |
| = | (134513.773 / 662542.645) | / | (136119.293 / 650526.349) |
| = | 0.203027 | / | 0.209245 |
| | = | 0.9703 |
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 - (103551.858 + 108352.923) / 441738.542) | / | (1 - (95708.799 + 68178.205) / 386071.352) |
| = | 0.520294 | / | 0.575501 |
| | = | 0.9041 |
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 |
| = | 650526.349 | / | 662542.645 |
| | = | 0.9819 |
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)) |
| = | (13556.659 / (13556.659 + 68178.205)) | / | (15095.796 / (15095.796 + 108352.923)) |
| = | 0.165861 | / | 0.122284 |
| | = | 1.3564 |
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) |
| = | (82073.155 / 650526.349) | / | (76380.151 / 662542.645) |
| = | 0.126164 | / | 0.115283 |
| | = | 1.0944 |
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) |
| = | ((9628.281 + 193546.7) / 441738.542) | / | ((3821.361 + 185884.607) / 386071.352) |
| = | 0.459944 | / | 0.491375 |
| | = | 0.936 |
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 |
| = | (-5560.297 - 0 | - | 22367.434) | / | 441738.542 |
| | = | -0.063222 |
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.
YES24 Co has a M-score of -2.92 suggests that the company is unlikely to be a manipulator.
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