F5 Beneish M-Score Historical Data
The historical data trend for F5'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.
F5 Beneish M-Score Chart
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F5 Annual Data
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Trend |
Sep15 |
Sep16 |
Sep17 |
Sep18 |
Sep19 |
Sep20 |
Sep21 |
Sep22 |
Sep23 |
Sep24 |
| Beneish M-Score |
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-2.79 |
-2.46 |
-2.20 |
-2.53 |
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F5 Quarterly Data
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Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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-2.53 |
-2.52 |
-2.70 |
-2.66 |
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Competitive Comparison of F5's Beneish M-Score
For the Software - Infrastructure subindustry, F5'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.
F5's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, F5's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where F5's Beneish M-Score falls into.
F5 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 F5 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 * 0.4688 | + | 0.528 * 0.9839 | + | 0.404 * 0.9784 | + | 0.892 * 1.001 | + | 0.115 * 0.9599 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9601 | + | 4.679 * -0.044936 | - | 0.327 * 0.9313 |
| = | -3.17 |
* 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 (Sep24) TTM: | Last Year (Sep23) TTM: |
Total Receivables was $389 Mil.
Revenue was 746.674 + 695.495 + 681.354 + 692.597 = $2,816 Mil.
Gross Profit was 602.954 + 559.07 + 540.241 + 556.208 = $2,258 Mil.
Total Current Assets was $2,109 Mil.
Total Assets was $5,613 Mil.
Property, Plant and Equipment(Net PPE) was $329 Mil.
Depreciation, Depletion and Amortization(DDA) was $107 Mil.
Selling, General, & Admin. Expense(SGA) was $1,097 Mil.
Total Current Liabilities was $1,490 Mil.
Long-Term Debt & Capital Lease Obligation was $216 Mil.
Net Income was 165.296 + 144.079 + 119.021 + 138.382 = $567 Mil.
Non Operating Income was 11.701 + 7.589 + 5.884 + 1.41 = $27 Mil.
Cash Flow from Operations was 246.505 + 158.959 + 221.637 + 165.318 = $792 Mil.
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Total Receivables was $829 Mil.
Revenue was 706.974 + 702.642 + 703.175 + 700.378 = $2,813 Mil.
Gross Profit was 566.01 + 560.959 + 547.521 + 545.371 = $2,220 Mil.
Total Current Assets was $1,849 Mil.
Total Assets was $5,248 Mil.
Property, Plant and Equipment(Net PPE) was $366 Mil.
Depreciation, Depletion and Amortization(DDA) was $113 Mil.
Selling, General, & Admin. Expense(SGA) was $1,142 Mil.
Total Current Liabilities was $1,473 Mil.
Long-Term Debt & Capital Lease Obligation was $240 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) |
| = | (389.024 / 2816.12) | / | (828.945 / 2813.169) |
| = | 0.138142 | / | 0.294666 |
| | = | 0.4688 |
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) |
| = | (2219.861 / 2813.169) | / | (2258.473 / 2816.12) |
| = | 0.789096 | / | 0.80198 |
| | = | 0.9839 |
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 - (2109.471 + 329.123) / 5613.004) | / | (1 - (1848.773 + 365.893) / 5248.333) |
| = | 0.565546 | / | 0.578025 |
| | = | 0.9784 |
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 |
| = | 2816.12 | / | 2813.169 |
| | = | 1.001 |
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)) |
| = | (112.702 / (112.702 + 365.893)) | / | (106.991 / (106.991 + 329.123)) |
| = | 0.235485 | / | 0.245328 |
| | = | 0.9599 |
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) |
| = | (1097.247 / 2816.12) | / | (1141.62 / 2813.169) |
| = | 0.389631 | / | 0.405813 |
| | = | 0.9601 |
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) |
| = | ((215.785 + 1489.653) / 5613.004) | / | ((239.565 + 1472.781) / 5248.333) |
| = | 0.303837 | / | 0.326265 |
| | = | 0.9313 |
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 |
| = | (566.778 - 26.584 | - | 792.419) | / | 5613.004 |
| | = | -0.044936 |
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.
F5 has a M-score of -3.17 suggests that the company is unlikely to be a manipulator.
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