CANCOM SE Beneish M-Score Historical Data
The historical data trend for CANCOM SE'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.
CANCOM SE Beneish M-Score Chart
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CANCOM SE Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.67 |
-2.31 |
-2.05 |
-1.82 |
-2.23 |
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CANCOM SE Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-1.82 |
-1.98 |
-1.74 |
-2.34 |
-2.23 |
Competitive Comparison of CANCOM SE's Beneish M-Score
For the Information Technology Services subindustry, CANCOM SE'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.
CANCOM SE's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, CANCOM SE's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where CANCOM SE's Beneish M-Score falls into.
CANCOM SE 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 CANCOM SE 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 * 1.048 | + | 0.528 * 0.8851 | + | 0.404 * 1.7048 | + | 0.892 * 1.1757 | + | 0.115 * 1.2632 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1 | + | 4.679 * -0.037329 | - | 0.327 * 1.0871 |
| = | -2.23 |
* 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 (Dec23) TTM: | Last Year (Dec22) TTM: |
Total Receivables was €529 Mil.
Revenue was 466.119 + 420.46 + 331.42 + 319.015 = €1,537 Mil.
Gross Profit was 174.493 + 161.704 + 128.184 + 116.984 = €581 Mil.
Total Current Assets was €911 Mil.
Total Assets was €1,548 Mil.
Property, Plant and Equipment(Net PPE) was €182 Mil.
Depreciation, Depletion and Amortization(DDA) was €60 Mil.
Selling, General, & Admin. Expense(SGA) was €0 Mil.
Total Current Liabilities was €599 Mil.
Long-Term Debt & Capital Lease Obligation was €146 Mil.
Net Income was 11.799 + 10.365 + 4.496 + 10.167 = €37 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = €0 Mil.
Cash Flow from Operations was 104.57 + 69.853 + -36.158 + -43.635 = €95 Mil.
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Total Receivables was €430 Mil.
Revenue was 370.889 + 334.312 + 301.944 + 300.217 = €1,307 Mil.
Gross Profit was 116.662 + 109.061 + 104.947 + 107.022 = €438 Mil.
Total Current Assets was €959 Mil.
Total Assets was €1,305 Mil.
Property, Plant and Equipment(Net PPE) was €121 Mil.
Depreciation, Depletion and Amortization(DDA) was €55 Mil.
Selling, General, & Admin. Expense(SGA) was €0 Mil.
Total Current Liabilities was €480 Mil.
Long-Term Debt & Capital Lease Obligation was €98 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) |
| = | (529.473 / 1537.014) | / | (429.724 / 1307.362) |
| = | 0.344482 | / | 0.328695 |
| | = | 1.048 |
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) |
| = | (437.692 / 1307.362) | / | (581.365 / 1537.014) |
| = | 0.33479 | / | 0.378243 |
| | = | 0.8851 |
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 - (911.137 + 181.844) / 1548.475) | / | (1 - (958.669 + 121.247) / 1305.106) |
| = | 0.294157 | / | 0.172545 |
| | = | 1.7048 |
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 |
| = | 1537.014 | / | 1307.362 |
| | = | 1.1757 |
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)) |
| = | (55.273 / (55.273 + 121.247)) | / | (59.932 / (59.932 + 181.844)) |
| = | 0.313126 | / | 0.247882 |
| | = | 1.2632 |
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 / 1537.014) | / | (0 / 1307.362) |
| = | 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) |
| = | ((145.875 + 599.172) / 1548.475) | / | ((97.88 + 479.764) / 1305.106) |
| = | 0.481149 | / | 0.442603 |
| | = | 1.0871 |
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 |
| = | (36.827 - 0 | - | 94.63) | / | 1548.475 |
| | = | -0.037329 |
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.
CANCOM SE has a M-score of -2.23 suggests that the company is unlikely to be a manipulator.
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