AerSale (ASLE) Operating Expenses (2018 - 2025)
AerSale (ASLE) posted Operating Expenses of $4.19 million for Q3 2025, down 3.7% from $4.35 million a year earlier and down 29.7% from the prior quarter.
Powered by 
Analysis
AerSale (ASLE) Operating Expenses (2018 - 2025) Analysis & Trends
For the trailing twelve months through Sep 30, 2025, Operating Expenses at AerSale was $22.14 million, down 47.3% year-over-year; for FY2024, it was $22.8 million, down 15.3% from FY2023.
- Annual Operating Expenses shows a five-year compound annual growth rate of 70.7% (FY2019 to FY2024).
- In prior years, AerSale's Operating Expenses was $26.93 million in FY2023 (+21.4%), $22.17 million in FY2022 (-71.4%), $77.5 million in FY2021 (+43.0%) and $54.2 million in FY2020.
- The Q3 2025 figure stands as the lowest quarterly Operating Expenses since Q3 2020.
- On a year-over-year basis, Operating Expenses has declined in each of the last seven quarters, with an average decline of 40.2% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q4 2021, with growth of 85.7%; the weakest was Q3 2024, with a decline of 82.9%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $5.96 million (Q2 2025), $5.74 million (Q1 2025) and $6.26 million (Q4 2024).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 330.21 Bn | 284.21 Bn | 4.68 Bn | 10.86 Bn |
| 2 | Rtx | 252.88 Bn | 226.09 Bn | 5.13 Bn | 21.96 Bn |
| 3 | Boeing | 145.76 Bn | 52.46 Bn | 2.41 Bn | 2.35 Bn |
| 4 | Lockheed Martin | 119.56 Bn | 106.28 Bn | 2.45 Bn | - |
| 5 | Howmet Aerospace | 91.38 Bn | 86.98 Bn | 951.00 Mn | 156.00 Mn |
| 6 | General Dynamics | 90.40 Bn | 77.51 Bn | 2.18 Bn | 12.63 Bn |
| 7 | Motorola Solutions | 74.81 Bn | 71.18 Bn | 1.68 Bn | 756.00 Mn |
| 8 | Northrop Grumman | 71.85 Bn | 61.10 Bn | 2.12 Bn | 9.78 Bn |
| 9 | Honeywell International | 67.04 Bn | 19.48 Bn | 3.65 Bn | 1.87 Bn |
| 10 | AerSale | 251.22 Mn | 231.13 Mn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2025 | 4.19 Mn |
| Jun 30, 2025 | 5.96 Mn |
| Mar 31, 2025 | 5.74 Mn |
| Dec 31, 2024 | 6.26 Mn |
| Sep 30, 2024 | 4.35 Mn |
| Jun 30, 2024 | 6.04 Mn |
| Mar 31, 2024 | 6.16 Mn |
| Dec 31, 2023 | 25.47 Mn |
| Sep 30, 2023 | 25.40 Mn |
| Jun 30, 2023 | 27.10 Mn |
| Mar 31, 2023 | 25.22 Mn |
| Dec 31, 2022 | 25.10 Mn |
| Sep 30, 2022 | 23.98 Mn |
| Jun 30, 2022 | 23.50 Mn |
| Mar 31, 2022 | 23.77 Mn |
| Dec 31, 2021 | 24.42 Mn |
| Sep 30, 2021 | 22.80 Mn |
| Jun 30, 2021 | 16.97 Mn |
| Mar 31, 2021 | 13.31 Mn |
| Dec 31, 2020 | 13.15 Mn |
API Access
AerSale 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=ASLE&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ASLE", "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=ASLE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();