B2En Co Beneish M-Score Historical Data
The historical data trend for B2En 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.
B2En Co Beneish M-Score Chart
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B2En Co Annual Data
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Trend |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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- |
- |
-3.04 |
-3.52 |
-3.28 |
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B2En Co Quarterly Data
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Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
| Beneish M-Score |
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-3.52 |
-3.42 |
-3.52 |
-3.00 |
-3.28 |
Competitive Comparison of B2En Co's Beneish M-Score
For the Shell Companies subindustry, B2En 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.
B2En Co's Beneish M-Score Distribution in the Diversified Financial Services Industry
For the Diversified Financial Services industry and Financial Services sector, B2En Co's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where B2En Co's Beneish M-Score falls into.
B2En 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 B2En 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 * 0.7826 | + | 0.528 * 1.2434 | + | 0.404 * 1.1994 | + | 0.892 * 0.7836 | + | 0.115 * 0.3842 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.7553 | + | 4.679 * -0.093395 | - | 0.327 * 0.9452 |
| = | -3.28 |
* 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 (Dec24) TTM: | Last Year (Dec23) TTM: |
Total Receivables was ₩2,291 Mil.
Revenue was 6790.326 + 5255.599 + 6442.737 + 6609.479 = ₩25,098 Mil.
Gross Profit was 2082.806 + 1141.809 + 1031.988 + 600.415 = ₩4,857 Mil.
Total Current Assets was ₩21,028 Mil.
Total Assets was ₩56,706 Mil.
Property, Plant and Equipment(Net PPE) was ₩2,579 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩176 Mil.
Selling, General, & Admin. Expense(SGA) was ₩2,882 Mil.
Total Current Liabilities was ₩13,477 Mil.
Long-Term Debt & Capital Lease Obligation was ₩7,140 Mil.
Net Income was 891.7 + -1346.654 + -4350.092 + -2148.28 = ₩-6,953 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 4450.849 + -2892.257 + 342.915 + -3558.804 = ₩-1,657 Mil.
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Total Receivables was ₩3,735 Mil.
Revenue was 10422.937 + 7525.047 + 5906.427 + 8175.112 = ₩32,030 Mil.
Gross Profit was 3597.103 + 2041.558 + 1195.97 + 872.287 = ₩7,707 Mil.
Total Current Assets was ₩9,555 Mil.
Total Assets was ₩28,607 Mil.
Property, Plant and Equipment(Net PPE) was ₩5,131 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩129 Mil.
Selling, General, & Admin. Expense(SGA) was ₩2,096 Mil.
Total Current Liabilities was ₩10,931 Mil.
Long-Term Debt & Capital Lease Obligation was ₩73 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) |
| = | (2290.777 / 25098.141) | / | (3735.331 / 32029.523) |
| = | 0.091273 | / | 0.116621 |
| | = | 0.7826 |
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) |
| = | (7706.918 / 32029.523) | / | (4857.018 / 25098.141) |
| = | 0.240619 | / | 0.193521 |
| | = | 1.2434 |
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 - (21028.167 + 2579.13) / 56705.86) | / | (1 - (9555.008 + 5130.988) / 28607.128) |
| = | 0.583689 | / | 0.486632 |
| | = | 1.1994 |
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 |
| = | 25098.141 | / | 32029.523 |
| | = | 0.7836 |
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)) |
| = | (129.06 / (129.06 + 5130.988)) | / | (175.969 / (175.969 + 2579.13)) |
| = | 0.024536 | / | 0.06387 |
| | = | 0.3842 |
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) |
| = | (2882.437 / 25098.141) | / | (2095.698 / 32029.523) |
| = | 0.114847 | / | 0.06543 |
| | = | 1.7553 |
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) |
| = | ((7139.52 + 13476.696) / 56705.86) | / | ((73.397 + 10930.663) / 28607.128) |
| = | 0.363564 | / | 0.384661 |
| | = | 0.9452 |
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 |
| = | (-6953.326 - 0 | - | -1657.297) | / | 56705.86 |
| | = | -0.093395 |
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.
B2En Co has a M-score of -3.28 suggests that the company is unlikely to be a manipulator.
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