Intercontinental Exchange (ICE) Operating Expenses (2013 - 2026)
Intercontinental Exchange (ICE) posted Operating Expenses of $1.28 billion for Q2 2026, up 2.3% from $1.25 billion a year earlier but down 2.8% from the prior quarter.
Intercontinental Exchange (ICE) Operating Expenses (2013 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Intercontinental Exchange was $5.09 billion, up 2.0% year-over-year; for FY2025, it came in at $5 billion, up 0.6% from FY2024.
- Annual Operating Expenses has increased for three consecutive years, with a five-year compound annual growth rate of 10.7% (FY2020 to FY2025).
- In prior years, Intercontinental Exchange's Operating Expenses was $4.97 billion in FY2024 (+15.7%), $4.29 billion in FY2023 (+17.5%), $3.65 billion in FY2022 (-1.2%) and $3.7 billion in FY2021 (+23.1%).
- Quarterly Operating Expenses has run from a low of $898 million in Q3 2022 to a high of $1.31 billion in Q1 2026 over five years.
- On a year-over-year basis, Operating Expenses has increased in each of the last three quarters, with growth averaging 1.9% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q4 2023, with growth of 41.2%; the weakest was Q4 2022, with a decline of 5.8%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $1.31 billion (Q1 2026), $1.27 billion (Q4 2025) and $1.24 billion (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Robinhood Markets | 104.48 Bn | 85.58 Bn | - | 734.00 Mn |
| 2 | Bank of New York Mellon | 99.71 Bn | 39.09 Bn | - | 3.44 Bn |
| 3 | Cme | 94.57 Bn | 94.57 Bn | - | 599.10 Mn |
| 4 | Intercontinental Exchange | 85.38 Bn | 79.19 Bn | - | 1.28 Bn |
| 5 | Nasdaq | 51.62 Bn | 49.05 Bn | 1.50 Bn | 788.00 Mn |
| 6 | State Street | 48.84 Bn | 48.84 Bn | - | 2.66 Bn |
| 7 | Interactive Brokers | 38.83 Bn | 32.29 Bn | - | 440.00 Mn |
| 8 | Northern Trust | 31.65 Bn | 31.65 Bn | - | 1.64 Bn |
| 9 | Cboe Global Markets | 27.38 Bn | 19.03 Bn | 731.60 Mn | 255.60 Mn |
| 10 | LPL Financial Holdings | 24.26 Bn | 19.58 Bn | - | 4.67 Bn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.28 Bn |
| Mar 31, 2026 | 1.31 Bn |
| Dec 31, 2025 | 1.27 Bn |
| Sep 30, 2025 | 1.24 Bn |
| Jun 30, 2025 | 1.25 Bn |
| Mar 31, 2025 | 1.25 Bn |
| Dec 31, 2024 | 1.25 Bn |
| Sep 30, 2024 | 1.25 Bn |
| Jun 30, 2024 | 1.25 Bn |
| Mar 31, 2024 | 1.23 Bn |
| Dec 31, 2023 | 1.28 Bn |
| Sep 30, 2023 | 1.16 Bn |
| Jun 30, 2023 | 933.00 Mn |
| Mar 31, 2023 | 927.00 Mn |
| Dec 31, 2022 | 904.00 Mn |
| Sep 30, 2022 | 898.00 Mn |
| Jun 30, 2022 | 945.00 Mn |
| Mar 31, 2022 | 907.00 Mn |
| Dec 31, 2021 | 960.00 Mn |
| Sep 30, 2021 | 924.00 Mn |
Intercontinental Exchange 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=ICE&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ICE", "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=ICE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();