Prevas AB Beneish M-Score Historical Data
The historical data trend for Prevas AB'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.
Prevas AB Beneish M-Score Chart
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Prevas AB Annual Data
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Trend |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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-3.34 |
-1.62 |
-2.13 |
-2.80 |
-2.38 |
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Prevas AB 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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-2.80 |
-2.82 |
-2.84 |
-2.14 |
-2.38 |
Competitive Comparison of Prevas AB's Beneish M-Score
For the Information Technology Services subindustry, Prevas AB'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.
Prevas AB's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Prevas AB's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Prevas AB's Beneish M-Score falls into.
Prevas AB 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 Prevas AB 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 * 1.0534 | + | 0.528 * 1.0607 | + | 0.404 * 1.259 | + | 0.892 * 1.0701 | + | 0.115 * 1.7633 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1 | + | 4.679 * -0.031599 | - | 0.327 * 1.2791 |
| = | -2.38 |
* 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 kr460 Mil.
Revenue was 432.007 + 351.903 + 395.629 + 407.087 = kr1,587 Mil.
Gross Profit was 165.558 + 136.465 + 159.486 + 176.097 = kr638 Mil.
Total Current Assets was kr508 Mil.
Total Assets was kr1,437 Mil.
Property, Plant and Equipment(Net PPE) was kr173 Mil.
Depreciation, Depletion and Amortization(DDA) was kr44 Mil.
Selling, General, & Admin. Expense(SGA) was kr0 Mil.
Total Current Liabilities was kr400 Mil.
Long-Term Debt & Capital Lease Obligation was kr246 Mil.
Net Income was 23.373 + 9.634 + 25.808 + 32.554 = kr91 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = kr0 Mil.
Cash Flow from Operations was 53.314 + -6.737 + 63.123 + 27.07 = kr137 Mil.
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Total Receivables was kr408 Mil.
Revenue was 399.281 + 311.359 + 377.651 + 394.347 = kr1,483 Mil.
Gross Profit was 169.958 + 128.986 + 150.415 + 182.6 = kr632 Mil.
Total Current Assets was kr553 Mil.
Total Assets was kr1,060 Mil.
Property, Plant and Equipment(Net PPE) was kr64 Mil.
Depreciation, Depletion and Amortization(DDA) was kr35 Mil.
Selling, General, & Admin. Expense(SGA) was kr0 Mil.
Total Current Liabilities was kr347 Mil.
Long-Term Debt & Capital Lease Obligation was kr26 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) |
| = | (460.436 / 1586.626) | / | (408.45 / 1482.638) |
| = | 0.290198 | / | 0.275489 |
| | = | 1.0534 |
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) |
| = | (631.959 / 1482.638) | / | (637.606 / 1586.626) |
| = | 0.42624 | / | 0.401863 |
| | = | 1.0607 |
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 - (507.734 + 173.271) / 1436.8) | / | (1 - (553.367 + 63.966) / 1060.366) |
| = | 0.526027 | / | 0.417811 |
| | = | 1.259 |
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 |
| = | 1586.626 | / | 1482.638 |
| | = | 1.0701 |
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)) |
| = | (35.413 / (35.413 + 63.966)) | / | (43.885 / (43.885 + 173.271)) |
| = | 0.356343 | / | 0.20209 |
| | = | 1.7633 |
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) |
| = | (0 / 1586.626) | / | (0 / 1482.638) |
| = | 0 | / | 0 |
| | = | 1 |
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) |
| = | ((246.12 + 400.119) / 1436.8) | / | ((26.329 + 346.522) / 1060.366) |
| = | 0.449777 | / | 0.351625 |
| | = | 1.2791 |
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 |
| = | (91.369 - 0 | - | 136.77) | / | 1436.8 |
| | = | -0.031599 |
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.
Prevas AB has a M-score of -2.38 suggests that the company is unlikely to be a manipulator.
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