Pegasystems Beneish M-Score Historical Data
The historical data trend for Pegasystems'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.
Pegasystems Beneish M-Score Chart
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Pegasystems Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.63 |
-2.68 |
-2.71 |
-3.51 |
-2.83 |
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Pegasystems Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-4.07 |
-3.49 |
-3.07 |
-2.83 |
-3.22 |
Competitive Comparison of Pegasystems's Beneish M-Score
For the Software - Application subindustry, Pegasystems'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.
Pegasystems's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Pegasystems's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Pegasystems's Beneish M-Score falls into.
Pegasystems 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 Pegasystems 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 * 0.7923 | + | 0.528 * 0.9491 | + | 0.404 * 0.8195 | + | 0.892 * 1.1344 | + | 0.115 * 0.893 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.7793 | + | 4.679 * -0.137078 | - | 0.327 * 0.8443 |
| = | -3.22 |
* 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 (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was $391 Mil.
Revenue was 330.147 + 474.233 + 334.643 + 298.268 = $1,437 Mil.
Gross Profit was 235.489 + 383.587 + 240.88 + 202.128 = $1,062 Mil.
Total Current Assets was $1,060 Mil.
Total Assets was $1,512 Mil.
Property, Plant and Equipment(Net PPE) was $106 Mil.
Depreciation, Depletion and Amortization(DDA) was $18 Mil.
Selling, General, & Admin. Expense(SGA) was $634 Mil.
Total Current Liabilities was $1,044 Mil.
Long-Term Debt & Capital Lease Obligation was $64 Mil.
Net Income was -12.124 + 142.665 + -7.279 + -46.804 = $76 Mil.
Non Operating Income was -30.845 + -2.442 + -11.739 + -1.116 = $-46 Mil.
Cash Flow from Operations was 180.146 + 79.865 + 24.168 + 45.645 = $330 Mil.
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Total Receivables was $435 Mil.
Revenue was 325.472 + 396.47 + 270.731 + 274.337 = $1,267 Mil.
Gross Profit was 227.538 + 304.197 + 177.681 + 179.222 = $889 Mil.
Total Current Assets was $796 Mil.
Total Assets was $1,282 Mil.
Property, Plant and Equipment(Net PPE) was $128 Mil.
Depreciation, Depletion and Amortization(DDA) was $19 Mil.
Selling, General, & Admin. Expense(SGA) was $717 Mil.
Total Current Liabilities was $475 Mil.
Long-Term Debt & Capital Lease Obligation was $638 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) |
| = | (390.661 / 1437.291) | / | (434.671 / 1267.01) |
| = | 0.271804 | / | 0.343068 |
| | = | 0.7923 |
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) |
| = | (888.638 / 1267.01) | / | (1062.084 / 1437.291) |
| = | 0.701366 | / | 0.738948 |
| | = | 0.9491 |
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 - (1059.587 + 106.368) / 1511.728) | / | (1 - (795.728 + 128.324) / 1281.841) |
| = | 0.228727 | / | 0.279121 |
| | = | 0.8195 |
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 |
| = | 1437.291 | / | 1267.01 |
| | = | 1.1344 |
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)) |
| = | (19.333 / (19.333 + 128.324)) | / | (18.276 / (18.276 + 106.368)) |
| = | 0.130932 | / | 0.146626 |
| | = | 0.893 |
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) |
| = | (634.235 / 1437.291) | / | (717.43 / 1267.01) |
| = | 0.441271 | / | 0.566239 |
| | = | 0.7793 |
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) |
| = | ((63.645 + 1044.279) / 1511.728) | / | ((637.737 + 474.964) / 1281.841) |
| = | 0.732886 | / | 0.868049 |
| | = | 0.8443 |
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 |
| = | (76.458 - -46.142 | - | 329.824) | / | 1511.728 |
| | = | -0.137078 |
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.
Pegasystems has a M-score of -3.22 suggests that the company is unlikely to be a manipulator.
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