Software AG Beneish M-Score Historical Data
The historical data trend for Software AG'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.
Software AG Beneish M-Score Chart
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Software AG Annual Data
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Trend |
Dec13 |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
| Beneish M-Score |
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-2.60 |
-2.51 |
-2.49 |
-3.76 |
-2.31 |
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Software AG Quarterly Data
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Dec18 |
Mar19 |
Jun19 |
Sep19 |
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Mar20 |
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Sep20 |
Dec20 |
Mar21 |
Jun21 |
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Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
| Beneish M-Score |
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-3.15 |
-2.31 |
-2.31 |
-2.44 |
-2.47 |
Competitive Comparison of Software AG's Beneish M-Score
For the Software - Infrastructure subindustry, Software AG'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.
Software AG's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Software AG's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Software AG's Beneish M-Score falls into.
Software AG 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 Software AG 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 * 1.0459 | + | 0.528 * 1.0179 | + | 0.404 * 1.0005 | + | 0.892 * 1.1151 | + | 0.115 * 1.0767 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9065 | + | 4.679 * 0.004451 | - | 0.327 * 1.3439 |
| = | -2.39 |
* 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 (Sep23) TTM: | Last Year (Sep22) TTM: |
Total Receivables was $265 Mil.
Revenue was 244.041 + 269.145 + 225.464 + 321.855 = $1,061 Mil.
Gross Profit was 181.864 + 205.157 + 160.085 + 243.123 = $790 Mil.
Total Current Assets was $788 Mil.
Total Assets was $2,760 Mil.
Property, Plant and Equipment(Net PPE) was $70 Mil.
Depreciation, Depletion and Amortization(DDA) was $63 Mil.
Selling, General, & Admin. Expense(SGA) was $443 Mil.
Total Current Liabilities was $716 Mil.
Long-Term Debt & Capital Lease Obligation was $0 Mil.
Net Income was 17.509 + 5.673 + 0.92 + -5.685 = $18 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = $0 Mil.
Cash Flow from Operations was 15.756 + -33.749 + 28.411 + -4.288 = $6 Mil.
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Total Receivables was $228 Mil.
Revenue was 219.219 + 239.858 + 226.907 + 265.069 = $951 Mil.
Gross Profit was 158.8 + 181.426 + 172.644 + 208.47 = $721 Mil.
Total Current Assets was $772 Mil.
Total Assets was $2,725 Mil.
Property, Plant and Equipment(Net PPE) was $76 Mil.
Depreciation, Depletion and Amortization(DDA) was $79 Mil.
Selling, General, & Admin. Expense(SGA) was $438 Mil.
Total Current Liabilities was $526 Mil.
Long-Term Debt & Capital Lease Obligation was $0 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) |
| = | (265.351 / 1060.505) | / | (227.523 / 951.053) |
| = | 0.250212 | / | 0.239233 |
| | = | 1.0459 |
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) |
| = | (721.34 / 951.053) | / | (790.229 / 1060.505) |
| = | 0.758465 | / | 0.745144 |
| | = | 1.0179 |
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 - (787.651 + 70.112) / 2760.211) | / | (1 - (772.253 + 75.603) / 2725.344) |
| = | 0.68924 | / | 0.688899 |
| | = | 1.0005 |
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 |
| = | 1060.505 | / | 951.053 |
| | = | 1.1151 |
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)) |
| = | (78.936 / (78.936 + 75.603)) | / | (63.284 / (63.284 + 70.112)) |
| = | 0.510784 | / | 0.474407 |
| | = | 1.0767 |
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) |
| = | (442.698 / 1060.505) | / | (437.96 / 951.053) |
| = | 0.417441 | / | 0.4605 |
| | = | 0.9065 |
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) |
| = | ((0 + 716.026) / 2760.211) | / | ((0 + 526.062) / 2725.344) |
| = | 0.25941 | / | 0.193026 |
| | = | 1.3439 |
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 |
| = | (18.417 - 0 | - | 6.13) | / | 2760.211 |
| | = | 0.004451 |
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.
Software AG has a M-score of -2.39 suggests that the company is unlikely to be a manipulator.
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