Geninus Beneish M-Score Historical Data
The historical data trend for Geninus'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.
Geninus Beneish M-Score Chart
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Geninus Annual Data
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Trend |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
- |
- |
4.82 |
0.65 |
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Geninus Quarterly Data
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Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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-2.43 |
0.65 |
-13.64 |
-4.83 |
-3.56 |
Competitive Comparison of Geninus's Beneish M-Score
For the Biotechnology subindustry, Geninus'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.
Geninus's Beneish M-Score Distribution in the Biotechnology Industry
For the Biotechnology industry and Healthcare sector, Geninus's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Geninus's Beneish M-Score falls into.
Geninus 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 Geninus 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 * 0.7803 | + | 0.528 * 1.1552 | + | 0.404 * 0.862 | + | 0.892 * 0.9685 | + | 0.115 * 1.0506 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.4151 | + | 4.679 * -0.069647 | - | 0.327 * 2.4759 |
| = | -3.56 |
* 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 (Sep24) TTM: | Last Year (Sep23) TTM: |
Total Receivables was ₩3,752 Mil.
Revenue was 1765.243 + 1471.845 + 1758.781 + 1709.37 = ₩6,705 Mil.
Gross Profit was 154.933 + 19.424 + 42.012 + -661.691 = ₩-445 Mil.
Total Current Assets was ₩19,761 Mil.
Total Assets was ₩34,996 Mil.
Property, Plant and Equipment(Net PPE) was ₩14,083 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩2,463 Mil.
Selling, General, & Admin. Expense(SGA) was ₩7,350 Mil.
Total Current Liabilities was ₩7,966 Mil.
Long-Term Debt & Capital Lease Obligation was ₩970 Mil.
Net Income was -1996.826 + -3914.331 + -2804.79 + -3352.345 = ₩-12,068 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was -2602.254 + -2175.327 + -4259.281 + -594.052 = ₩-9,631 Mil.
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Total Receivables was ₩4,965 Mil.
Revenue was 1463.512 + 1899.738 + 1894.572 + 1665.419 = ₩6,923 Mil.
Gross Profit was 12.466 + 588.308 + 144.123 + -1276.059 = ₩-531 Mil.
Total Current Assets was ₩29,917 Mil.
Total Assets was ₩41,724 Mil.
Property, Plant and Equipment(Net PPE) was ₩10,213 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩1,893 Mil.
Selling, General, & Admin. Expense(SGA) was ₩5,363 Mil.
Total Current Liabilities was ₩3,022 Mil.
Long-Term Debt & Capital Lease Obligation was ₩1,281 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) |
| = | (3752.262 / 6705.239) | / | (4965.245 / 6923.241) |
| = | 0.559602 | / | 0.717185 |
| | = | 0.7803 |
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) |
| = | (-531.162 / 6923.241) | / | (-445.322 / 6705.239) |
| = | -0.076722 | / | -0.066414 |
| | = | 1.1552 |
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 - (19760.874 + 14082.782) / 34996.114) | / | (1 - (29916.99 + 10213.431) / 41724.397) |
| = | 0.032931 | / | 0.038202 |
| | = | 0.862 |
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 |
| = | 6705.239 | / | 6923.241 |
| | = | 0.9685 |
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)) |
| = | (1893.199 / (1893.199 + 10213.431)) | / | (2462.805 / (2462.805 + 14082.782)) |
| = | 0.156377 | / | 0.14885 |
| | = | 1.0506 |
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) |
| = | (7350.423 / 6705.239) | / | (5363.255 / 6923.241) |
| = | 1.096221 | / | 0.774674 |
| | = | 1.4151 |
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) |
| = | ((970.202 + 7965.684) / 34996.114) | / | ((1281.397 + 3021.655) / 41724.397) |
| = | 0.255339 | / | 0.10313 |
| | = | 2.4759 |
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 |
| = | (-12068.292 - 0 | - | -9630.914) | / | 34996.114 |
| | = | -0.069647 |
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.
Geninus has a M-score of -3.56 suggests that the company is unlikely to be a manipulator.
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