Arista Networks Beneish M-Score Historical Data
The historical data trend for Arista 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.
|
Arista Networks Annual Data
|
|
Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
|
|
|
|
|
|
-2.14 |
-2.58 |
-2.47 |
-1.16 |
-2.35 |
|
Arista Networks Quarterly Data
|
|
Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
-1.16 |
-1.48 |
-1.71 |
-2.04 |
-2.35 |
Competitive Comparison
For the Computer Hardware subindustry, Arista 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.
Arista Networks Beneish M-Score Distribution
For the Hardware industry and Technology sector, Arista Networks's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Arista Networks's Beneish M-Score falls into.
Arista 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 Arista 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 * 0.8298 | + | 0.528 * 0.9858 | + | 0.404 * 0.8773 | + | 0.892 * 1.3375 | + | 0.115 * 0.9693 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9219 | + | 4.679 * 0.004117 | - | 0.327 * 0.9725 |
| = | -2.35 |
* 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 $1,025 Mil.
Revenue was 1540.437 + 1509.456 + 1458.924 + 1351.351 = $5,860 Mil.
Gross Profit was 999.226 + 942.419 + 884.129 + 804.507 = $3,630 Mil.
Total Current Assets was $8,390 Mil.
Total Assets was $9,947 Mil.
Property, Plant and Equipment(Net PPE) was $102 Mil.
Depreciation, Depletion and Amortization(DDA) was $71 Mil.
Selling, General, & Admin. Expense(SGA) was $518 Mil.
Total Current Liabilities was $1,910 Mil.
Long-Term Debt & Capital Lease Obligation was $0 Mil.
Net Income was 613.636 + 545.327 + 491.885 + 436.473 = $2,087 Mil.
Non Operating Income was 0.447 + -1.861 + 24.133 + -10.363 = $12 Mil.
Cash Flow from Operations was 526.464 + 698.977 + 434.09 + 374.483 = $2,034 Mil.
|
Total Receivables was $923 Mil.
Revenue was 1275.552 + 1176.801 + 1051.891 + 877.066 = $4,381 Mil.
Gross Profit was 768.606 + 709.98 + 643.265 + 553.845 = $2,676 Mil.
Total Current Assets was $5,551 Mil.
Total Assets was $6,775 Mil.
Property, Plant and Equipment(Net PPE) was $95 Mil.
Depreciation, Depletion and Amortization(DDA) was $63 Mil.
Selling, General, & Admin. Expense(SGA) was $420 Mil.
Total Current Liabilities was $1,294 Mil.
Long-Term Debt & Capital Lease Obligation was $44 Mil.
|
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) |
| = | (1024.569 / 5860.168) | / | (923.096 / 4381.31) |
| = | 0.174836 | / | 0.210689 |
| | = | 0.8298 |
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) |
| = | (2675.696 / 4381.31) | / | (3630.281 / 5860.168) |
| = | 0.610707 | / | 0.619484 |
| | = | 0.9858 |
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 - (8390.235 + 101.58) / 9946.806) | / | (1 - (5550.748 + 95.009) / 6775.41) |
| = | 0.146277 | / | 0.166728 |
| | = | 0.8773 |
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 |
| = | 5860.168 | / | 4381.31 |
| | = | 1.3375 |
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)) |
| = | (62.7 / (62.7 + 95.009)) | / | (70.63 / (70.63 + 101.58)) |
| = | 0.397568 | / | 0.410139 |
| | = | 0.9693 |
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) |
| = | (518.114 / 5860.168) | / | (420.196 / 4381.31) |
| = | 0.088413 | / | 0.095906 |
| | = | 0.9219 |
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) |
| = | ((0 + 1909.606) / 9946.806) | / | ((43.964 + 1293.531) / 6775.41) |
| = | 0.191982 | / | 0.197404 |
| | = | 0.9725 |
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 |
| = | (2087.321 - 12.356 | - | 2034.014) | / | 9946.806 |
| | = | 0.004117 |
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.
Arista Networks has a M-score of -2.35 suggests that the company is unlikely to be a manipulator.
Quick Browse
Personalize
Premium Gurus 
Create New Portfolio
Portfolio Contest
ANET has been successfully added to your