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 |
Sep14 |
Sep15 |
Sep16 |
Sep17 |
Sep18 |
Sep19 |
Sep20 |
Sep21 |
Sep22 |
Sep23 |
| Beneish M-Score |
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-2.51 |
-2.79 |
-2.46 |
-2.20 |
-2.53 |
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F5 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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-2.37 |
-2.36 |
-2.51 |
-2.53 |
-2.52 |
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 * 1.0461 | + | 0.528 * 0.9979 | + | 0.404 * 0.9662 | + | 0.892 * 1.0355 | + | 0.115 * 0.9254 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8836 | + | 4.679 * -0.028725 | - | 0.327 * 0.9288 |
| = | -2.52 |
* 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 $887 Mil.
Revenue was 692.597 + 706.974 + 702.642 + 703.175 = $2,805 Mil.
Gross Profit was 556.208 + 566.01 + 560.959 + 547.521 = $2,231 Mil.
Total Current Assets was $1,962 Mil.
Total Assets was $5,349 Mil.
Property, Plant and Equipment(Net PPE) was $359 Mil.
Depreciation, Depletion and Amortization(DDA) was $114 Mil.
Selling, General, & Admin. Expense(SGA) was $1,102 Mil.
Total Current Liabilities was $1,524 Mil.
Long-Term Debt & Capital Lease Obligation was $235 Mil.
Net Income was 138.382 + 152.134 + 88.976 + 81.436 = $461 Mil.
Non Operating Income was 1.41 + 3.085 + -53.752 + 2.737 = $-47 Mil.
Cash Flow from Operations was 165.318 + 189.801 + 165.054 + 140.923 = $661 Mil.
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Total Receivables was $819 Mil.
Revenue was 700.378 + 700.033 + 674.488 + 634.224 = $2,709 Mil.
Gross Profit was 545.371 + 552.571 + 543.755 + 507.865 = $2,150 Mil.
Total Current Assets was $1,715 Mil.
Total Assets was $5,086 Mil.
Property, Plant and Equipment(Net PPE) was $392 Mil.
Depreciation, Depletion and Amortization(DDA) was $113 Mil.
Selling, General, & Admin. Expense(SGA) was $1,205 Mil.
Total Current Liabilities was $1,533 Mil.
Long-Term Debt & Capital Lease Obligation was $268 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) |
| = | (887.285 / 2805.388) | / | (819.093 / 2709.123) |
| = | 0.316279 | / | 0.302346 |
| | = | 1.0461 |
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) |
| = | (2149.562 / 2709.123) | / | (2230.698 / 2805.388) |
| = | 0.793453 | / | 0.795148 |
| | = | 0.9979 |
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 - (1961.751 + 359.287) / 5348.855) | / | (1 - (1714.507 + 391.662) / 5085.568) |
| = | 0.566068 | / | 0.585854 |
| | = | 0.9662 |
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 |
| = | 2805.388 | / | 2709.123 |
| | = | 1.0355 |
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)) |
| = | (112.821 / (112.821 + 391.662)) | / | (114.496 / (114.496 + 359.287)) |
| = | 0.223637 | / | 0.241663 |
| | = | 0.9254 |
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) |
| = | (1102.169 / 2805.388) | / | (1204.549 / 2709.123) |
| = | 0.392876 | / | 0.444627 |
| | = | 0.8836 |
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) |
| = | ((235.001 + 1524.46) / 5348.855) | / | ((267.7 + 1533.479) / 5085.568) |
| = | 0.328942 | / | 0.354175 |
| | = | 0.9288 |
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 |
| = | (460.928 - -46.52 | - | 661.096) | / | 5348.855 |
| | = | -0.028725 |
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 -2.52 suggests that the company is unlikely to be a manipulator.
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