F5 (FFIV) Accumulated Expenses (2009 - 2026)
F5's Accumulated Expenses was $344.44 million in fiscal Q3 2026 (quarter ended Jun 30, 2026), up 22.4% from $281.41 million a year earlier and up 4.7% from the prior quarter.
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Analysis
F5 (FFIV) Accumulated Expenses (2009 - 2026) Analysis & Trends
At the end of FY2025 (ended Sep 30, 2025), Accumulated Expenses at F5 came in at $315.38 million, up 5.1% from FY2024.
- Accumulated Expenses shows a five-year compound annual growth rate of -0.4% (FY2020 to FY2025).
- In earlier fiscal years, Accumulated Expenses was $300.08 million in FY2024 (+6.1%), $282.89 million in FY2023 (-8.7%), $309.82 million in FY2022 (-9.3%) and $341.49 million in FY2021 (+6.3%).
- The fiscal Q3 2026 figure marks the highest quarterly Accumulated Expenses in data going back to fiscal Q4 2009.
- Compared with a year earlier, Accumulated Expenses was higher in seven of the last eight quarters, with growth averaging 9.3%.
- The best year-over-year quarter for Accumulated Expenses over five years was fiscal Q3 2026 (growth of 22.4%); the worst was fiscal Q1 2024 (a decline of 15.6%).
- Per Business Quant data, FFIV's Accumulated Expenses in the three fiscal quarters before Q3 2026 was $329.07 million (Q2 2026), $305.19 million (Q1 2026) and $315.38 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Palo Alto Networks | 323.81 Bn | 308.88 Bn | 2.30 Bn |
| 2 | CrowdStrike Holdings | 271.09 Bn | 251.53 Bn | 1.10 Bn |
| 3 | Fortinet | 131.14 Bn | 117.07 Bn | 1.64 Bn |
| 4 | Snowflake | 119.71 Bn | 107.03 Bn | 1.04 Bn |
| 5 | Datadog | 98.30 Bn | 79.94 Bn | 881.34 Mn |
| 6 | Okta | 34.95 Bn | 25.05 Bn | 641.00 Mn |
| 7 | Axon Enterprise | 34.32 Bn | 28.85 Bn | 546.45 Mn |
| 8 | Zscaler | 32.52 Bn | 18.64 Bn | - |
| 9 | Baidu | 29.56 Bn | -44.07 Bn | 1.47 Mn |
| 10 | F5 | 25.30 Bn | 19.71 Bn | 711.51 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 344.44 Mn |
| Mar 31, 2026 | 329.07 Mn |
| Dec 31, 2025 | 305.19 Mn |
| Sep 30, 2025 | 315.38 Mn |
| Jun 30, 2025 | 281.41 Mn |
| Mar 31, 2025 | 279.91 Mn |
| Dec 31, 2024 | 316.37 Mn |
| Sep 30, 2024 | 300.08 Mn |
| Jun 30, 2024 | 259.87 Mn |
| Mar 31, 2024 | 266.56 Mn |
| Dec 31, 2023 | 278.92 Mn |
| Sep 30, 2023 | 282.89 Mn |
| Jun 30, 2023 | 274.26 Mn |
| Mar 31, 2023 | 295.53 Mn |
| Dec 31, 2022 | 330.52 Mn |
| Sep 30, 2022 | 309.82 Mn |
| Jun 30, 2022 | 291.61 Mn |
| Mar 31, 2022 | 301.21 Mn |
| Dec 31, 2021 | 314.85 Mn |
| Sep 30, 2021 | 341.49 Mn |
API Access
F5 Accumulated Expenses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=FFIV&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "FFIV", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=FFIV&period=max&api_key=YOUR_API_KEY");
const data = await res.json();