Dynatrace Beneish M-Score Historical Data
The historical data trend for Dynatrace'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.
Dynatrace Beneish M-Score Chart
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Dynatrace Annual Data
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Trend |
Mar17 |
Mar18 |
Mar19 |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
| Beneish M-Score |
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- |
-2.33 |
-2.47 |
-2.55 |
-2.71 |
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Dynatrace 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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-2.83 |
-2.71 |
-2.56 |
-2.40 |
-2.58 |
Competitive Comparison of Dynatrace's Beneish M-Score
For the Software - Application subindustry, Dynatrace'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.
Dynatrace's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Dynatrace's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Dynatrace's Beneish M-Score falls into.
Dynatrace 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 Dynatrace 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 * 0.9551 | + | 0.528 * 0.9922 | + | 0.404 * 0.8783 | + | 0.892 * 1.2439 | + | 0.115 * 0.9785 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.963 | + | 4.679 * -0.055153 | - | 0.327 * 0.9187 |
| = | -2.58 |
* 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 $362 Mil.
Revenue was 365.096 + 351.7 + 332.886 + 314.475 = $1,364 Mil.
Gross Profit was 297.227 + 287.333 + 270.542 + 254.91 = $1,110 Mil.
Total Current Assets was $1,287 Mil.
Total Assets was $2,999 Mil.
Property, Plant and Equipment(Net PPE) was $115 Mil.
Depreciation, Depletion and Amortization(DDA) was $55 Mil.
Selling, General, & Admin. Expense(SGA) was $680 Mil.
Total Current Liabilities was $959 Mil.
Long-Term Debt & Capital Lease Obligation was $58 Mil.
Net Income was 42.691 + 35.809 + 38.188 + 80.293 = $197 Mil.
Non Operating Income was -3.9 + -3.074 + 0.251 + 2.256 = $-4 Mil.
Cash Flow from Operations was 75.657 + 36.877 + 133.903 + 120.427 = $367 Mil.
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Total Receivables was $304 Mil.
Revenue was 297.456 + 279.326 + 267.273 + 252.585 = $1,097 Mil.
Gross Profit was 241.632 + 223.622 + 215.475 + 204.669 = $885 Mil.
Total Current Assets was $831 Mil.
Total Assets was $2,414 Mil.
Property, Plant and Equipment(Net PPE) was $119 Mil.
Depreciation, Depletion and Amortization(DDA) was $55 Mil.
Selling, General, & Admin. Expense(SGA) was $567 Mil.
Total Current Liabilities was $831 Mil.
Long-Term Debt & Capital Lease Obligation was $60 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) |
| = | (361.653 / 1364.157) | / | (304.411 / 1096.64) |
| = | 0.265111 | / | 0.277585 |
| | = | 0.9551 |
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) |
| = | (885.398 / 1096.64) | / | (1110.012 / 1364.157) |
| = | 0.807373 | / | 0.813698 |
| | = | 0.9922 |
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 - (1286.662 + 115.303) / 2999.213) | / | (1 - (830.897 + 119.258) / 2413.879) |
| = | 0.532556 | / | 0.606378 |
| | = | 0.8783 |
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 |
| = | 1364.157 | / | 1096.64 |
| | = | 1.2439 |
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)) |
| = | (54.984 / (54.984 + 119.258)) | / | (54.881 / (54.881 + 115.303)) |
| = | 0.315561 | / | 0.32248 |
| | = | 0.9785 |
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) |
| = | (679.768 / 1364.157) | / | (567.466 / 1096.64) |
| = | 0.498306 | / | 0.517459 |
| | = | 0.963 |
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) |
| = | ((58.002 + 958.588) / 2999.213) | / | ((59.589 + 831.017) / 2413.879) |
| = | 0.338952 | / | 0.368952 |
| | = | 0.9187 |
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 |
| = | (196.981 - -4.467 | - | 366.864) | / | 2999.213 |
| | = | -0.055153 |
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.
Dynatrace has a M-score of -2.58 suggests that the company is unlikely to be a manipulator.
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