FTAI Aviation (FTAI) Operating Expenses (2014 - 2026)
FTAI Aviation (FTAI) posted Operating Expenses of $758.28 million for Q2 2026, up 62.8% from $465.75 million a year earlier and up 14.8% from the prior quarter.
FTAI Aviation (FTAI) Operating Expenses (2014 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at FTAI Aviation was $2.37 billion, up 60.6% year-over-year; for FY2025, it came in at $1.77 billion, up 18.0% from FY2024.
- Annual Operating Expenses has increased for five consecutive years, with a five-year compound annual growth rate of 39.7% (FY2020 to FY2025).
- In prior years, FTAI Aviation's Operating Expenses was $1.5 billion in FY2024 (+80.1%), $831.22 million in FY2023 (+33.1%), $624.51 million in FY2022 (+49.0%) and $419.19 million in FY2021 (+26.2%).
- The Q2 2026 figure stands as the highest quarterly Operating Expenses in data going back to Q1 2014.
- On a year-over-year basis, Operating Expenses has increased in each of the last four quarters, with growth averaging 46.5% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q3 2022, with growth of 261.2%; the weakest was Q4 2022, with a decline of 99.9%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $660.32 million (Q1 2026), $483.06 million (Q4 2025) and $466.19 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 303.54 Bn | 262.06 Bn | 5.02 Bn | 11.75 Bn |
| 2 | Rtx | 262.72 Bn | 230.99 Bn | 5.81 Bn | 21.79 Bn |
| 3 | Boeing | 148.13 Bn | 54.82 Bn | 2.41 Bn | 2.35 Bn |
| 4 | Lockheed Martin | 135.78 Bn | 122.50 Bn | 2.45 Bn | - |
| 5 | General Dynamics | 94.57 Bn | 81.69 Bn | 2.18 Bn | 12.63 Bn |
| 6 | Motorola Solutions | 79.37 Bn | 75.71 Bn | 1.68 Bn | 756.00 Mn |
| 7 | Northrop Grumman | 78.67 Bn | 66.13 Bn | 2.35 Bn | 9.85 Bn |
| 8 | Howmet Aerospace | 77.61 Bn | 73.21 Bn | 951.00 Mn | 156.00 Mn |
| 9 | Honeywell International | 69.07 Bn | 21.20 Bn | 3.65 Bn | 1.87 Bn |
| 10 | FTAI Aviation | 16.09 Bn | 14.53 Bn | 317.30 Mn | 758.28 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 758.28 Mn |
| Mar 31, 2026 | 660.32 Mn |
| Dec 31, 2025 | 483.06 Mn |
| Sep 30, 2025 | 466.19 Mn |
| Jun 30, 2025 | 465.75 Mn |
| Mar 31, 2025 | 351.12 Mn |
| Dec 31, 2024 | 340.61 Mn |
| Sep 30, 2024 | 316.52 Mn |
| Jun 30, 2024 | 606.19 Mn |
| Mar 31, 2024 | 233.76 Mn |
| Dec 31, 2023 | 224.88 Mn |
| Sep 30, 2023 | 206.41 Mn |
| Jun 30, 2023 | 217.77 Mn |
| Mar 31, 2023 | 259.97 Mn |
| Dec 31, 2022 | 177,000.00 |
| Sep 30, 2022 | 209.07 Mn |
| Jun 30, 2022 | 129.34 Mn |
| Mar 31, 2022 | 285.92 Mn |
| Dec 31, 2021 | 265.09 Mn |
| Sep 30, 2021 | 57.88 Mn |
FTAI Aviation Operating 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=operating-expenses&ticker=FTAI&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "FTAI", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=FTAI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();