One4u Co Beneish M-Score Historical Data
The historical data trend for One4u 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.
One4u Co Beneish M-Score Chart
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One4u Co Annual Data
|
|
Trend |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
|
- |
- |
-2.89 |
|
One4u Co Semi-Annual Data
|
|
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
- |
- |
-2.89 |
Competitive Comparison of One4u Co's Beneish M-Score
For the Telecom Services subindustry, One4u 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.
One4u Co's Beneish M-Score Distribution in the Telecommunication Services Industry
For the Telecommunication Services industry and Communication Services sector, One4u Co's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where One4u Co's Beneish M-Score falls into.
One4u 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 One4u 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 * 0.5027 | + | 0.528 * 0.642 | + | 0.404 * 0.835 | + | 0.892 * 1.7542 | + | 0.115 * 0.98 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.604 | + | 4.679 * -0.096447 | - | 0.327 * 0.9645 |
| = | -2.89 |
* 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 ₩241 Mil.
Revenue was ₩10,126 Mil.
Gross Profit was ₩4,889 Mil.
Total Current Assets was ₩7,066 Mil.
Total Assets was ₩22,288 Mil.
Property, Plant and Equipment(Net PPE) was ₩5,867 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩785 Mil.
Selling, General, & Admin. Expense(SGA) was ₩462 Mil.
Total Current Liabilities was ₩10,272 Mil.
Long-Term Debt & Capital Lease Obligation was ₩0 Mil.
Net Income was ₩2,518 Mil.
Gross Profit was ₩0 Mil.
Cash Flow from Operations was ₩4,668 Mil.
|
Total Receivables was ₩273 Mil.
Revenue was ₩5,772 Mil.
Gross Profit was ₩1,789 Mil.
Total Current Assets was ₩2,745 Mil.
Total Assets was ₩18,694 Mil.
Property, Plant and Equipment(Net PPE) was ₩6,552 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩857 Mil.
Selling, General, & Admin. Expense(SGA) was ₩436 Mil.
Total Current Liabilities was ₩8,933 Mil.
Long-Term Debt & Capital Lease Obligation was ₩0 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) |
| = | (240.6 / 10125.555) | / | (272.839 / 5772.309) |
| = | 0.023762 | / | 0.047267 |
| | = | 0.5027 |
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) |
| = | (1789.366 / 5772.309) | / | (4889.131 / 10125.555) |
| = | 0.309991 | / | 0.482851 |
| | = | 0.642 |
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 - (7065.845 + 5867.482) / 22288.346) | / | (1 - (2745.395 + 6551.67) / 18694.369) |
| = | 0.419727 | / | 0.502681 |
| | = | 0.835 |
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 |
| = | 10125.555 | / | 5772.309 |
| | = | 1.7542 |
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)) |
| = | (856.672 / (856.672 + 6551.67)) | / | (784.995 / (784.995 + 5867.482)) |
| = | 0.115636 | / | 0.118 |
| | = | 0.98 |
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) |
| = | (462.191 / 10125.555) | / | (436.246 / 5772.309) |
| = | 0.045646 | / | 0.075576 |
| | = | 0.604 |
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) |
| = | ((0 + 10271.813) / 22288.346) | / | ((0 + 8932.697) / 18694.369) |
| = | 0.46086 | / | 0.477828 |
| | = | 0.9645 |
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 |
| = | (2518.485 - 0 | - | 4668.122) | / | 22288.346 |
| | = | -0.096447 |
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.
One4u Co has a M-score of -2.89 suggests that the company is unlikely to be a manipulator.
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