Nutanix Beneish M-Score Historical Data
The historical data trend for Nutanix'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.
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Nutanix Annual Data
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Trend |
Jul13 |
Jul14 |
Jul15 |
Jul16 |
Jul17 |
Jul18 |
Jul19 |
Jul20 |
Jul21 |
Jul22 |
| Beneish M-Score |
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-3.27 |
-4.24 |
-4.38 |
-4.14 |
-3.93 |
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Nutanix Quarterly Data
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Jan18 |
Apr18 |
Jul18 |
Oct18 |
Jan19 |
Apr19 |
Jul19 |
Oct19 |
Jan20 |
Apr20 |
Jul20 |
Oct20 |
Jan21 |
Apr21 |
Jul21 |
Oct21 |
Jan22 |
Apr22 |
Jul22 |
Oct22 |
| Beneish M-Score |
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-4.05 |
-3.71 |
-3.39 |
-3.93 |
-3.90 |
Competitive Comparison
For the Software - Infrastructure subindustry, Nutanix'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.
Nutanix Beneish M-Score Distribution
For the Software industry and Technology sector, Nutanix's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Nutanix's Beneish M-Score falls in comparison to its industry or sector. The grey bar indicates the Beneish M-Score's extreme value range as defined by GuruFocus.
Nutanix 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 Nutanix 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 * 0.6446 | + | 0.528 * 0.9848 | + | 0.404 * 0.9196 | + | 0.892 * 1.1204 | + | 0.115 * 1.086 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8422 | + | 4.679 * -0.2542 | - | 0.327 * 1.0253 |
| = | -3.90 |
* 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 (Oct22) TTM: | Last Year (Oct21) TTM: |
Total Receivables was $90 Mil.
Revenue was 433.609 + 385.54 + 403.658 + 413.081 = $1,636 Mil.
Gross Profit was 351.114 + 305.648 + 323.809 + 333.112 = $1,314 Mil.
Total Current Assets was $1,672 Mil.
Total Assets was $2,357 Mil.
Property, Plant and Equipment(Net PPE) was $223 Mil.
Depreciation, Depletion and Amortization(DDA) was $85 Mil.
Selling, General, & Admin. Expense(SGA) was $1,137 Mil.
Total Current Liabilities was $1,148 Mil.
Long-Term Debt & Capital Lease Obligation was $1,258 Mil.
Net Income was -99.116 + -150.99 + -111.635 + -115.061 = $-477 Mil.
Non Operating Income was -3.198 + 1.686 + -1.474 + -0.728 = $-4 Mil.
Cash Flow from Operations was 65.513 + 38.004 + -3.167 + 25.767 = $126 Mil.
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Total Receivables was $125 Mil.
Revenue was 378.517 + 390.72 + 344.508 + 346.382 = $1,460 Mil.
Gross Profit was 297.071 + 312.201 + 270.034 + 275.428 = $1,155 Mil.
Total Current Assets was $1,552 Mil.
Total Assets was $2,255 Mil.
Property, Plant and Equipment(Net PPE) was $221 Mil.
Depreciation, Depletion and Amortization(DDA) was $94 Mil.
Selling, General, & Admin. Expense(SGA) was $1,205 Mil.
Total Current Liabilities was $905 Mil.
Long-Term Debt & Capital Lease Obligation was $1,339 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) |
| = | (90 / 1635.888) | / | (124.628 / 1460.127) |
| = | 0.05501599 | / | 0.08535422 |
| | = | 0.6446 |
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) |
| = | (1154.734 / 1460.127) | / | (1313.683 / 1635.888) |
| = | 0.79084491 | / | 0.80303969 |
| | = | 0.9848 |
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 - (1672.095 + 222.883) / 2357.422) | / | (1 - (1552.395 + 221.261) / 2254.566) |
| = | 0.19616513 | / | 0.21330491 |
| | = | 0.9196 |
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 |
| = | 1635.888 | / | 1460.127 |
| | = | 1.1204 |
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)) |
| = | (94.165 / (94.165 + 221.261)) | / | (84.5 / (84.5 + 222.883)) |
| = | 0.29853278 | / | 0.27490134 |
| | = | 1.086 |
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) |
| = | (1137.237 / 1635.888) | / | (1205.287 / 1460.127) |
| = | 0.69518023 | / | 0.82546724 |
| | = | 0.8422 |
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) |
| = | ((1258.079 + 1147.799) / 2357.422) | / | ((1339.331 + 904.787) / 2254.566) |
| = | 1.02055466 | / | 0.99536585 |
| | = | 1.0253 |
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 |
| = | (-476.802 - -3.714 | - | 126.117) | / | 2357.422 |
| | = | -0.2542 |
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.
Nutanix has a M-score of -3.90 suggests that the company is unlikely to be a manipulator.
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