PowerSchool Holdings Beneish M-Score Historical Data
The historical data trend for PowerSchool Holdings'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.
PowerSchool Holdings Beneish M-Score Chart
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PowerSchool Holdings Annual Data
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Trend |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
- |
-2.58 |
-2.61 |
-2.44 |
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PowerSchool Holdings Quarterly Data
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Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.61 |
-2.72 |
-2.38 |
-2.51 |
-2.44 |
Competitive Comparison of PowerSchool Holdings's Beneish M-Score
For the Software - Application subindustry, PowerSchool Holdings'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.
PowerSchool Holdings's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, PowerSchool Holdings's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where PowerSchool Holdings's Beneish M-Score falls into.
PowerSchool Holdings 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 PowerSchool Holdings 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 * 1.2757 | + | 0.528 * 0.958 | + | 0.404 * 1.0227 | + | 0.892 * 1.1062 | + | 0.115 * 1.035 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0889 | + | 4.679 * -0.053034 | - | 0.327 * 1.1065 |
| = | -2.44 |
* 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 $76.6 Mil.
Revenue was 182.136 + 182.164 + 173.897 + 159.454 = $697.7 Mil.
Gross Profit was 108.631 + 110.314 + 104.868 + 89.965 = $413.8 Mil.
Total Current Assets was $156.1 Mil.
Total Assets was $3,776.9 Mil.
Property, Plant and Equipment(Net PPE) was $21.0 Mil.
Depreciation, Depletion and Amortization(DDA) was $134.3 Mil.
Selling, General, & Admin. Expense(SGA) was $214.8 Mil.
Total Current Liabilities was $516.9 Mil.
Long-Term Debt & Capital Lease Obligation was $824.7 Mil.
Net Income was -15.616 + -0.473 + -3.195 + -11.853 = $-31.1 Mil.
Non Operating Income was 1.142 + -2.494 + -0.031 + -0.044 = $-1.4 Mil.
Cash Flow from Operations was 42.943 + 220.392 + -32.714 + -60.027 = $170.6 Mil.
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Total Receivables was $54.3 Mil.
Revenue was 161.066 + 162.434 + 157.591 + 149.592 = $630.7 Mil.
Gross Profit was 94.466 + 92.647 + 89.606 + 81.615 = $358.3 Mil.
Total Current Assets was $228.7 Mil.
Total Assets was $3,583.4 Mil.
Property, Plant and Equipment(Net PPE) was $15.1 Mil.
Depreciation, Depletion and Amortization(DDA) was $128.3 Mil.
Selling, General, & Admin. Expense(SGA) was $178.3 Mil.
Total Current Liabilities was $413.7 Mil.
Long-Term Debt & Capital Lease Obligation was $736.7 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) |
| = | (76.618 / 697.651) | / | (54.296 / 630.683) |
| = | 0.109823 | / | 0.086091 |
| | = | 1.2757 |
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) |
| = | (358.334 / 630.683) | / | (413.778 / 697.651) |
| = | 0.568168 | / | 0.593102 |
| | = | 0.958 |
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 - (156.121 + 21.001) / 3776.882) | / | (1 - (228.653 + 15.05) / 3583.395) |
| = | 0.953104 | / | 0.931991 |
| | = | 1.0227 |
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 |
| = | 697.651 | / | 630.683 |
| | = | 1.1062 |
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)) |
| = | (128.269 / (128.269 + 15.05)) | / | (134.251 / (134.251 + 21.001)) |
| = | 0.894989 | / | 0.86473 |
| | = | 1.035 |
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) |
| = | (214.807 / 697.651) | / | (178.336 / 630.683) |
| = | 0.3079 | / | 0.282766 |
| | = | 1.0889 |
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) |
| = | ((824.684 + 516.909) / 3776.882) | / | ((736.677 + 413.697) / 3583.395) |
| = | 0.355212 | / | 0.321029 |
| | = | 1.1065 |
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 |
| = | (-31.137 - -1.427 | - | 170.594) | / | 3776.882 |
| | = | -0.053034 |
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.
PowerSchool Holdings has a M-score of -2.44 suggests that the company is unlikely to be a manipulator.
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