Vuno Beneish M-Score Historical Data
The historical data trend for Vuno'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.
Vuno Beneish M-Score Chart
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Vuno Annual Data
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Trend |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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- |
-0.83 |
-0.30 |
-1.86 |
0.92 |
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Vuno 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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-1.86 |
-2.52 |
-2.49 |
-2.87 |
0.92 |
Competitive Comparison of Vuno's Beneish M-Score
For the Health Information Services subindustry, Vuno'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.
Vuno's Beneish M-Score Distribution in the Healthcare Providers & Services Industry
For the Healthcare Providers & Services industry and Healthcare sector, Vuno's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Vuno's Beneish M-Score falls into.
Vuno 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 Vuno 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 * 3.9823 | + | 0.528 * 0.9479 | + | 0.404 * 0.6668 | + | 0.892 * 1.9486 | + | 0.115 * 0.8606 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8713 | + | 4.679 * -0.043088 | - | 0.327 * 0.5001 |
| = | 0.92 |
* 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 ₩28,236 Mil.
Revenue was 7075.577 + 6865.356 + 6390.218 + 5538.269 = ₩25,869 Mil.
Gross Profit was 6950.638 + 6661.448 + 6075.836 + 5362.114 = ₩25,050 Mil.
Total Current Assets was ₩40,513 Mil.
Total Assets was ₩50,182 Mil.
Property, Plant and Equipment(Net PPE) was ₩2,993 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩1,529 Mil.
Selling, General, & Admin. Expense(SGA) was ₩20,291 Mil.
Total Current Liabilities was ₩16,095 Mil.
Long-Term Debt & Capital Lease Obligation was ₩1,814 Mil.
Net Income was -3065.262 + -2837.526 + -3220.751 + -3894.908 = ₩-13,018 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was -2851.436 + -2009.691 + -3753.6 + -2241.444 = ₩-10,856 Mil.
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Total Receivables was ₩3,639 Mil.
Revenue was 4925.912 + 3568.168 + 3005.312 + 1776.5 = ₩13,276 Mil.
Gross Profit was 4725.958 + 3261.307 + 2670.156 + 1528.025 = ₩12,185 Mil.
Total Current Assets was ₩14,602 Mil.
Total Assets was ₩22,556 Mil.
Property, Plant and Equipment(Net PPE) was ₩3,453 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩1,418 Mil.
Selling, General, & Admin. Expense(SGA) was ₩11,951 Mil.
Total Current Liabilities was ₩11,123 Mil.
Long-Term Debt & Capital Lease Obligation was ₩4,972 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) |
| = | (28236.324 / 25869.42) | / | (3638.719 / 13275.892) |
| = | 1.091494 | / | 0.274085 |
| | = | 3.9823 |
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) |
| = | (12185.446 / 13275.892) | / | (25050.036 / 25869.42) |
| = | 0.917863 | / | 0.968326 |
| | = | 0.9479 |
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 - (40512.67 + 2992.691) / 50182.43) | / | (1 - (14601.746 + 3453.396) / 22556.171) |
| = | 0.133056 | / | 0.199548 |
| | = | 0.6668 |
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 |
| = | 25869.42 | / | 13275.892 |
| | = | 1.9486 |
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)) |
| = | (1417.594 / (1417.594 + 3453.396)) | / | (1529.178 / (1529.178 + 2992.691)) |
| = | 0.291028 | / | 0.338174 |
| | = | 0.8606 |
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) |
| = | (20290.939 / 25869.42) | / | (11951.387 / 13275.892) |
| = | 0.78436 | / | 0.900232 |
| | = | 0.8713 |
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) |
| = | ((1814.469 + 16094.933) / 50182.43) | / | ((4972.324 + 11123.002) / 22556.171) |
| = | 0.356886 | / | 0.713566 |
| | = | 0.5001 |
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 |
| = | (-13018.447 - 0 | - | -10856.171) | / | 50182.43 |
| | = | -0.043088 |
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.
Vuno has a M-score of 0.92 signals that the company is likely to be a manipulator.
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