Cboe Global Markets (CBOE) Operating Expenses (2010 - 2026)
Cboe Global Markets' Operating Expenses was $255.6 million in Q2 2026, up 3.0% from $248.2 million a year earlier and up 14.5% from the prior quarter.
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Analysis
Cboe Global Markets (CBOE) Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Cboe Global Markets' Operating Expenses was $981.4 million through Jun 30, 2026, up 7.8% year-over-year; for FY2025, it was $962 million, down 1.2% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 10.2% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $974 million in FY2024 (+13.2%), $860.1 million in FY2023 (-31.3%), $1.25 billion in FY2022 (+86.8%) and $670.2 million in FY2021 (+13.2%).
- Quarterly Operating Expenses has moved between $169.9 million (Q4 2021) and $661.5 million (Q2 2022) over five years.
- Compared with a year earlier, Operating Expenses has increased for four straight quarters, with growth averaging 3.4% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q2 2022 (growth of 311.9%); the worst was Q2 2023 (a decline of 66.4%).
- Per Business Quant data, CBOE's Operating Expenses in the three quarters before Q2 2026 was $223.3 million (Q1 2026), $267.3 million (Q4 2025) and $235.2 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Robinhood Markets | 101.14 Bn | 82.23 Bn | - | 734.00 Mn |
| 2 | Bank of New York Mellon | 98.14 Bn | 37.51 Bn | - | 3.44 Bn |
| 3 | Cme | 94.12 Bn | 94.12 Bn | - | 599.10 Mn |
| 4 | Intercontinental Exchange | 85.35 Bn | 79.16 Bn | - | 1.28 Bn |
| 5 | Nasdaq | 51.71 Bn | 49.14 Bn | 1.50 Bn | 788.00 Mn |
| 6 | State Street | 47.94 Bn | 47.94 Bn | - | 2.66 Bn |
| 7 | Interactive Brokers | 38.49 Bn | 31.95 Bn | - | 440.00 Mn |
| 8 | Northern Trust | 30.99 Bn | 30.99 Bn | - | 1.64 Bn |
| 9 | Cboe Global Markets | 28.76 Bn | 20.41 Bn | 731.60 Mn | 255.60 Mn |
| 10 | LPL Financial Holdings | 24.08 Bn | 19.40 Bn | - | 4.67 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 255.60 Mn |
| Mar 31, 2026 | 223.30 Mn |
| Dec 31, 2025 | 267.30 Mn |
| Sep 30, 2025 | 235.20 Mn |
| Jun 30, 2025 | 248.20 Mn |
| Mar 31, 2025 | 211.30 Mn |
| Dec 31, 2024 | 226.00 Mn |
| Sep 30, 2024 | 224.60 Mn |
| Jun 30, 2024 | 303.70 Mn |
| Mar 31, 2024 | 219.70 Mn |
| Dec 31, 2023 | 205.00 Mn |
| Sep 30, 2023 | 209.30 Mn |
| Jun 30, 2023 | 222.30 Mn |
| Mar 31, 2023 | 223.50 Mn |
| Dec 31, 2022 | 206.60 Mn |
| Sep 30, 2022 | 205.60 Mn |
| Jun 30, 2022 | 661.50 Mn |
| Mar 31, 2022 | 178.40 Mn |
| Dec 31, 2021 | 169.90 Mn |
| Sep 30, 2021 | 178.80 Mn |
API Access
Cboe Global Markets 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=CBOE&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "CBOE", "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=CBOE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();