Juniper Networks Beneish M-Score Historical Data
The historical data trend for Juniper 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.
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Juniper Networks Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.28 |
-2.53 |
-2.63 |
-2.10 |
-2.80 |
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Juniper Networks 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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-2.10 |
-2.08 |
-2.69 |
-2.82 |
-2.80 |
Competitive Comparison
For the Communication Equipment subindustry, Juniper 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.
Juniper Networks Beneish M-Score Distribution
For the Hardware industry and Technology sector, Juniper Networks's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Juniper Networks's Beneish M-Score falls into.
Juniper 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 Juniper 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 * 0.8105 | + | 0.528 * 0.9698 | + | 0.404 * 0.9839 | + | 0.892 * 1.0497 | + | 0.115 * 1.0853 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0261 | + | 4.679 * -0.039176 | - | 0.327 * 0.9813 |
| = | -2.80 |
* 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 $1,044 Mil.
Revenue was 1364.8 + 1397.8 + 1430.1 + 1371.8 = $5,565 Mil.
Gross Profit was 807.2 + 810.4 + 813.1 + 771.2 = $3,202 Mil.
Total Current Assets was $3,796 Mil.
Total Assets was $9,519 Mil.
Property, Plant and Equipment(Net PPE) was $801 Mil.
Depreciation, Depletion and Amortization(DDA) was $195 Mil.
Selling, General, & Admin. Expense(SGA) was $1,489 Mil.
Total Current Liabilities was $2,104 Mil.
Long-Term Debt & Capital Lease Obligation was $1,700 Mil.
Net Income was 124.3 + 76.1 + 24.4 + 85.4 = $310 Mil.
Non Operating Income was -22.3 + -60.9 + -108.1 + 1.6 = $-190 Mil.
Cash Flow from Operations was 9.1 + 329.2 + 343 + 191.5 = $873 Mil.
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Total Receivables was $1,227 Mil.
Revenue was 1448.8 + 1414.6 + 1269.6 + 1168.2 = $5,301 Mil.
Gross Profit was 827 + 787.8 + 694.1 + 649.4 = $2,958 Mil.
Total Current Assets was $3,617 Mil.
Total Assets was $9,327 Mil.
Property, Plant and Equipment(Net PPE) was $808 Mil.
Depreciation, Depletion and Amortization(DDA) was $218 Mil.
Selling, General, & Admin. Expense(SGA) was $1,383 Mil.
Total Current Liabilities was $2,079 Mil.
Long-Term Debt & Capital Lease Obligation was $1,719 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) |
| = | (1044.1 / 5564.5) | / | (1227.3 / 5301.2) |
| = | 0.187636 | / | 0.231514 |
| | = | 0.8105 |
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) |
| = | (2958.3 / 5301.2) | / | (3201.9 / 5564.5) |
| = | 0.558043 | / | 0.575416 |
| | = | 0.9698 |
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 - (3795.5 + 801.3) / 9518.5) | / | (1 - (3617.1 + 808.4) / 9326.7) |
| = | 0.517067 | / | 0.525502 |
| | = | 0.9839 |
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 |
| = | 5564.5 | / | 5301.2 |
| | = | 1.0497 |
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)) |
| = | (217.7 / (217.7 + 808.4)) | / | (194.7 / (194.7 + 801.3)) |
| = | 0.212163 | / | 0.195482 |
| | = | 1.0853 |
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) |
| = | (1489.4 / 5564.5) | / | (1382.9 / 5301.2) |
| = | 0.267661 | / | 0.260865 |
| | = | 1.0261 |
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) |
| = | ((1699.7 + 2104) / 9518.5) | / | ((1719 + 2078.9) / 9326.7) |
| = | 0.399611 | / | 0.407207 |
| | = | 0.9813 |
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 |
| = | (310.2 - -189.7 | - | 872.8) | / | 9518.5 |
| | = | -0.039176 |
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.
Juniper Networks has a M-score of -2.80 suggests that the company is unlikely to be a manipulator.
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