ELUON Beneish M-Score Historical Data
The historical data trend for ELUON'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.
ELUON Beneish M-Score Chart
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ELUON Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.71 |
-2.97 |
-2.97 |
-2.36 |
-2.87 |
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ELUON Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.36 |
-2.15 |
-2.52 |
-2.20 |
-2.87 |
Competitive Comparison of ELUON's Beneish M-Score
For the Telecom Services subindustry, ELUON'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.
ELUON's Beneish M-Score Distribution in the Telecommunication Services Industry
For the Telecommunication Services industry and Communication Services sector, ELUON's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where ELUON's Beneish M-Score falls into.
ELUON 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 ELUON 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 * 0.7451 | + | 0.528 * 0.8545 | + | 0.404 * 1.0617 | + | 0.892 * 0.9907 | + | 0.115 * 1.0752 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0858 | + | 4.679 * -0.02925 | - | 0.327 * 0.8656 |
| = | -2.87 |
* 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 ₩7,767 Mil.
Revenue was 25698.421 + 10012.638 + 11207.531 + 9114.938 = ₩56,034 Mil.
Gross Profit was 7331.516 + 2900.186 + 3430.634 + 3002.786 = ₩16,665 Mil.
Total Current Assets was ₩50,624 Mil.
Total Assets was ₩64,397 Mil.
Property, Plant and Equipment(Net PPE) was ₩10,195 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩499 Mil.
Selling, General, & Admin. Expense(SGA) was ₩1,896 Mil.
Total Current Liabilities was ₩18,325 Mil.
Long-Term Debt & Capital Lease Obligation was ₩0 Mil.
Net Income was 3366.236 + -129.46 + 437.989 + 53.391 = ₩3,728 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 8824.678 + -1197.969 + 2546.023 + -4560.983 = ₩5,612 Mil.
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Total Receivables was ₩10,522 Mil.
Revenue was 26860.173 + 9623.602 + 10156.473 + 9921.524 = ₩56,562 Mil.
Gross Profit was 5303.724 + 2702.662 + 2968.21 + 3399.495 = ₩14,374 Mil.
Total Current Assets was ₩50,823 Mil.
Total Assets was ₩64,561 Mil.
Property, Plant and Equipment(Net PPE) was ₩10,358 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩547 Mil.
Selling, General, & Admin. Expense(SGA) was ₩1,762 Mil.
Total Current Liabilities was ₩21,224 Mil.
Long-Term Debt & Capital Lease Obligation was ₩0 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) |
| = | (7767.075 / 56033.528) | / | (10521.871 / 56561.772) |
| = | 0.138615 | / | 0.186024 |
| | = | 0.7451 |
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) |
| = | (14374.091 / 56561.772) | / | (16665.122 / 56033.528) |
| = | 0.254131 | / | 0.297413 |
| | = | 0.8545 |
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 - (50624.307 + 10194.652) / 64397.145) | / | (1 - (50823.201 + 10358.386) / 64560.516) |
| = | 0.055564 | / | 0.052337 |
| | = | 1.0617 |
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 |
| = | 56033.528 | / | 56561.772 |
| | = | 0.9907 |
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)) |
| = | (547.107 / (547.107 + 10358.386)) | / | (498.977 / (498.977 + 10194.652)) |
| = | 0.050168 | / | 0.046661 |
| | = | 1.0752 |
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) |
| = | (1895.606 / 56033.528) | / | (1762.338 / 56561.772) |
| = | 0.03383 | / | 0.031158 |
| | = | 1.0858 |
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 + 18324.672) / 64397.145) | / | ((0 + 21224.125) / 64560.516) |
| = | 0.284557 | / | 0.328748 |
| | = | 0.8656 |
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 |
| = | (3728.156 - 0 | - | 5611.749) | / | 64397.145 |
| | = | -0.02925 |
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.
ELUON has a M-score of -2.87 suggests that the company is unlikely to be a manipulator.
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