Hypera Beneish M-Score Historical Data
The historical data trend for Hypera'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.
Hypera Beneish M-Score Chart
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Hypera Annual Data
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Trend |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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-2.54 |
-2.06 |
-2.37 |
-2.60 |
-2.79 |
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Hypera 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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-2.60 |
-2.55 |
-2.54 |
-2.67 |
-2.79 |
Competitive Comparison of Hypera's Beneish M-Score
For the Drug Manufacturers - Specialty & Generic subindustry, Hypera'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.
Hypera's Beneish M-Score Distribution in the Drug Manufacturers Industry
For the Drug Manufacturers industry and Healthcare sector, Hypera's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Hypera's Beneish M-Score falls into.
Hypera 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 Hypera 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 * 0.9058 | + | 0.528 * 1.0722 | + | 0.404 * 1.0834 | + | 0.892 * 0.9403 | + | 0.115 * 0.9343 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1328 | + | 4.679 * -0.048805 | - | 0.327 * 0.955 |
| = | -2.79 |
* 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 R$2,255 Mil.
Revenue was 1510.991 + 1915.906 + 2188.909 + 1826.66 = R$7,442 Mil.
Gross Profit was 786.44 + 1145.714 + 1333.532 + 1115.313 = R$4,381 Mil.
Total Current Assets was R$6,682 Mil.
Total Assets was R$24,559 Mil.
Property, Plant and Equipment(Net PPE) was R$3,891 Mil.
Depreciation, Depletion and Amortization(DDA) was R$281 Mil.
Selling, General, & Admin. Expense(SGA) was R$2,042 Mil.
Total Current Liabilities was R$3,940 Mil.
Long-Term Debt & Capital Lease Obligation was R$7,988 Mil.
Net Income was 79.558 + 376.378 + 492.814 + 392.24 = R$1,341 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = R$0 Mil.
Cash Flow from Operations was 698.198 + 738.07 + 624.165 + 479.166 = R$2,540 Mil.
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Total Receivables was R$2,647 Mil.
Revenue was 1846.925 + 2138.461 + 2231.077 + 1698.195 = R$7,915 Mil.
Gross Profit was 1146.422 + 1353.811 + 1409.202 + 1086.109 = R$4,996 Mil.
Total Current Assets was R$8,078 Mil.
Total Assets was R$24,509 Mil.
Property, Plant and Equipment(Net PPE) was R$3,548 Mil.
Depreciation, Depletion and Amortization(DDA) was R$238 Mil.
Selling, General, & Admin. Expense(SGA) was R$1,917 Mil.
Total Current Liabilities was R$4,644 Mil.
Long-Term Debt & Capital Lease Obligation was R$7,821 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) |
| = | (2254.672 / 7442.466) | / | (2646.941 / 7914.658) |
| = | 0.302947 | / | 0.334435 |
| | = | 0.9058 |
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) |
| = | (4995.544 / 7914.658) | / | (4380.999 / 7442.466) |
| = | 0.631176 | / | 0.588649 |
| | = | 1.0722 |
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 - (6681.876 + 3891.156) / 24559.083) | / | (1 - (8077.766 + 3548.04) / 24508.751) |
| = | 0.569486 | / | 0.525647 |
| | = | 1.0834 |
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 |
| = | 7442.466 | / | 7914.658 |
| | = | 0.9403 |
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)) |
| = | (238.312 / (238.312 + 3548.04)) | / | (281.055 / (281.055 + 3891.156)) |
| = | 0.06294 | / | 0.067364 |
| | = | 0.9343 |
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) |
| = | (2041.506 / 7442.466) | / | (1916.504 / 7914.658) |
| = | 0.274305 | / | 0.242146 |
| | = | 1.1328 |
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) |
| = | ((7988.364 + 3940.088) / 24559.083) | / | ((7820.84 + 4644.236) / 24508.751) |
| = | 0.485704 | / | 0.508597 |
| | = | 0.955 |
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 |
| = | (1340.99 - 0 | - | 2539.599) | / | 24559.083 |
| | = | -0.048805 |
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.
Hypera has a M-score of -2.79 suggests that the company is unlikely to be a manipulator.
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