Daebongls Co Beneish M-Score Historical Data
The historical data trend for Daebongls 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.
Daebongls Co Beneish M-Score Chart
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Daebongls 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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-2.87 |
-2.84 |
-2.23 |
-2.64 |
-2.01 |
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Daebongls Co Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
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Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-2.44 |
-2.65 |
-2.15 |
-2.01 |
-2.50 |
Competitive Comparison of Daebongls Co's Beneish M-Score
For the Chemicals subindustry, Daebongls 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.
Daebongls Co's Beneish M-Score Distribution in the Chemicals Industry
For the Chemicals industry and Basic Materials sector, Daebongls Co's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Daebongls Co's Beneish M-Score falls into.
Daebongls 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 Daebongls 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 * 1.0803 | + | 0.528 * 1.0296 | + | 0.404 * 1.1252 | + | 0.892 * 0.9537 | + | 0.115 * 1.2123 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1248 | + | 4.679 * -0.01677 | - | 0.327 * 1.1404 |
| = | -2.50 |
* 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 ₩26,230 Mil.
Revenue was 22986.569 + 22342.165 + 21951.347 + 21295.028 = ₩88,575 Mil.
Gross Profit was 6374.681 + 6106.315 + 5308.855 + 4449.299 = ₩22,239 Mil.
Total Current Assets was ₩110,571 Mil.
Total Assets was ₩195,229 Mil.
Property, Plant and Equipment(Net PPE) was ₩52,097 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩3,439 Mil.
Selling, General, & Admin. Expense(SGA) was ₩3,031 Mil.
Total Current Liabilities was ₩42,500 Mil.
Long-Term Debt & Capital Lease Obligation was ₩308 Mil.
Net Income was 983.854 + 1877.379 + 263.896 + 393.226 = ₩3,518 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 3051.248 + 2000.749 + 238.604 + 1501.69 = ₩6,792 Mil.
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Total Receivables was ₩25,459 Mil.
Revenue was 22033.664 + 23957.956 + 21848.956 + 25039.118 = ₩92,880 Mil.
Gross Profit was 5580.219 + 6591.415 + 5466.571 + 6372.987 = ₩24,011 Mil.
Total Current Assets was ₩119,894 Mil.
Total Assets was ₩187,011 Mil.
Property, Plant and Equipment(Net PPE) was ₩39,397 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩3,197 Mil.
Selling, General, & Admin. Expense(SGA) was ₩2,826 Mil.
Total Current Liabilities was ₩34,127 Mil.
Long-Term Debt & Capital Lease Obligation was ₩1,831 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) |
| = | (26229.644 / 88575.109) | / | (25459.472 / 92879.694) |
| = | 0.296129 | / | 0.274112 |
| | = | 1.0803 |
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) |
| = | (24011.192 / 92879.694) | / | (22239.15 / 88575.109) |
| = | 0.258519 | / | 0.251077 |
| | = | 1.0296 |
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 - (110570.57 + 52096.557) / 195228.81) | / | (1 - (119893.912 + 39396.731) / 187011.48) |
| = | 0.166787 | / | 0.148231 |
| | = | 1.1252 |
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 |
| = | 88575.109 | / | 92879.694 |
| | = | 0.9537 |
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)) |
| = | (3197.189 / (3197.189 + 39396.731)) | / | (3438.654 / (3438.654 + 52096.557)) |
| = | 0.075062 | / | 0.061918 |
| | = | 1.2123 |
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) |
| = | (3031.281 / 88575.109) | / | (2825.848 / 92879.694) |
| = | 0.034223 | / | 0.030425 |
| | = | 1.1248 |
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) |
| = | ((307.914 + 42499.793) / 195228.81) | / | ((1830.78 + 34126.742) / 187011.48) |
| = | 0.219269 | / | 0.192274 |
| | = | 1.1404 |
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 |
| = | (3518.355 - 0 | - | 6792.291) | / | 195228.81 |
| | = | -0.01677 |
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.
Daebongls Co has a M-score of -2.50 suggests that the company is unlikely to be a manipulator.
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