Extreme Networks Beneish M-Score Historical Data
The historical data trend for Extreme Networks'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.
Extreme Networks Beneish M-Score Chart
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Extreme Networks Annual Data
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| Beneish M-Score |
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-3.44 |
-3.17 |
-2.90 |
-2.57 |
-3.17 |
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Extreme Networks Quarterly Data
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Mar19 |
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Dec23 |
| Beneish M-Score |
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-2.92 |
-3.23 |
-3.17 |
-3.34 |
-3.27 |
Competitive Comparison of Extreme Networks's Beneish M-Score
For the Communication Equipment subindustry, Extreme Networks'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.
Extreme Networks's Beneish M-Score Distribution in the Hardware Industry
For the Hardware industry and Technology sector, Extreme Networks's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Extreme Networks's Beneish M-Score falls into.
Extreme Networks 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 Extreme Networks 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 * 0.6459 | + | 0.528 * 0.9437 | + | 0.404 * 0.9365 | + | 0.892 * 1.1409 | + | 0.115 * 1.3308 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0183 | + | 4.679 * -0.126241 | - | 0.327 * 0.9221 |
| = | -3.27 |
* 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 $112 Mil.
Revenue was 296.377 + 353.137 + 363.91 + 332.507 = $1,346 Mil.
Gross Profit was 183.37 + 212.936 + 214.419 + 191.938 = $803 Mil.
Total Current Assets was $558 Mil.
Total Assets was $1,143 Mil.
Property, Plant and Equipment(Net PPE) was $95 Mil.
Depreciation, Depletion and Amortization(DDA) was $30 Mil.
Selling, General, & Admin. Expense(SGA) was $452 Mil.
Total Current Liabilities was $549 Mil.
Long-Term Debt & Capital Lease Obligation was $227 Mil.
Net Income was 3.988 + 28.676 + 25.427 + 22.131 = $80 Mil.
Non Operating Income was -9.594 + -2.285 + -0.659 + -1.73 = $-14 Mil.
Cash Flow from Operations was 34.23 + 75.635 + 80.693 + 48.182 = $239 Mil.
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Total Receivables was $152 Mil.
Revenue was 318.348 + 297.689 + 278.196 + 285.508 = $1,180 Mil.
Gross Profit was 181.655 + 166.708 + 154.191 + 161.358 = $664 Mil.
Total Current Assets was $498 Mil.
Total Assets was $1,062 Mil.
Property, Plant and Equipment(Net PPE) was $78 Mil.
Depreciation, Depletion and Amortization(DDA) was $36 Mil.
Selling, General, & Admin. Expense(SGA) was $389 Mil.
Total Current Liabilities was $529 Mil.
Long-Term Debt & Capital Lease Obligation was $253 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) |
| = | (112.047 / 1345.931) | / | (152.05 / 1179.741) |
| = | 0.083249 | / | 0.128884 |
| | = | 0.6459 |
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) |
| = | (663.912 / 1179.741) | / | (802.663 / 1345.931) |
| = | 0.562761 | / | 0.596363 |
| | = | 0.9437 |
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 - (558.243 + 94.722) / 1142.658) | / | (1 - (497.665 + 78.443) / 1062.176) |
| = | 0.428556 | / | 0.457615 |
| | = | 0.9365 |
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 |
| = | 1345.931 | / | 1179.741 |
| | = | 1.1409 |
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)) |
| = | (36.37 / (36.37 + 78.443)) | / | (29.59 / (29.59 + 94.722)) |
| = | 0.316776 | / | 0.23803 |
| | = | 1.3308 |
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) |
| = | (451.619 / 1345.931) | / | (388.747 / 1179.741) |
| = | 0.335544 | / | 0.329519 |
| | = | 1.0183 |
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) |
| = | ((226.783 + 548.966) / 1142.658) | / | ((252.944 + 529.102) / 1062.176) |
| = | 0.678899 | / | 0.736268 |
| | = | 0.9221 |
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 |
| = | (80.222 - -14.268 | - | 238.74) | / | 1142.658 |
| | = | -0.126241 |
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.
Extreme Networks has a M-score of -3.27 suggests that the company is unlikely to be a manipulator.
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