Cboe Global Markets (CBOE) EBITDA (2010 - 2026)
Cboe Global Markets' EBITDA came in at $504.1 million for Q2 2026, up 36.6% from $369 million a year earlier but down 5.8% from the prior quarter.
Cboe Global Markets (CBOE) EBITDA (2010 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Cboe Global Markets reported EBITDA of $1.88 billion, up 31.8% year-over-year; for FY2025, it came in at $1.59 billion, up 29.1% from FY2024.
- EBITDA has increased in each of the last three years, with a five-year compound annual growth rate of 14.1% (FY2020 to FY2025).
- Going back by year, EBITDA was $1.23 billion in FY2024 (+1.3%), $1.22 billion in FY2023 (+85.2%), $656.4 million in FY2022 (-32.6%) and $973.3 million in FY2021 (+18.6%).
- The five-year range for quarterly EBITDA is -$197.2 million (Q2 2022) to $535.1 million (Q1 2026).
- Year-over-year, EBITDA has increased for six consecutive quarters, with growth averaging 25.9% over the last eight quarters.
- The fastest year-over-year change in EBITDA over five years came in Q2 2025 (growth of 52.5%), and the weakest in Q2 2024 (a decline of 15.0%).
- Business Quant data shows CBOE's EBITDA at $535.1 million (Q1 2026), $435.1 million (Q4 2025) and $401.2 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Robinhood Markets | 104.70 Bn | 85.79 Bn | - | 891.00 Mn |
| 2 | Bank of New York Mellon | 100.72 Bn | 40.09 Bn | - | 7.16 Bn |
| 3 | Cme | 94.58 Bn | 94.58 Bn | - | 1.19 Bn |
| 4 | Intercontinental Exchange | 85.83 Bn | 79.63 Bn | - | 1.78 Bn |
| 5 | Nasdaq | 52.05 Bn | 49.49 Bn | 1.50 Bn | 877.00 Mn |
| 6 | State Street | 49.39 Bn | 49.39 Bn | - | 3.57 Bn |
| 7 | Interactive Brokers | 39.24 Bn | 32.69 Bn | - | 2.65 Bn |
| 8 | Northern Trust | 31.94 Bn | 31.94 Bn | - | 2.78 Bn |
| 9 | Cboe Global Markets | 26.47 Bn | 18.13 Bn | 731.60 Mn | 504.10 Mn |
| 10 | LPL Financial Holdings | 24.62 Bn | 19.94 Bn | - | 797.71 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 504.10 Mn |
| Mar 31, 2026 | 535.10 Mn |
| Dec 31, 2025 | 435.10 Mn |
| Sep 30, 2025 | 401.20 Mn |
| Jun 30, 2025 | 369.00 Mn |
| Mar 31, 2025 | 384.20 Mn |
| Dec 31, 2024 | 330.60 Mn |
| Sep 30, 2024 | 339.20 Mn |
| Jun 30, 2024 | 241.90 Mn |
| Mar 31, 2024 | 319.70 Mn |
| Dec 31, 2023 | 332.00 Mn |
| Sep 30, 2023 | 310.00 Mn |
| Jun 30, 2023 | 284.60 Mn |
| Mar 31, 2023 | 289.30 Mn |
| Dec 31, 2022 | 295.20 Mn |
| Sep 30, 2022 | 277.80 Mn |
| Jun 30, 2022 | -197.20 Mn |
| Mar 31, 2022 | 280.60 Mn |
| Dec 31, 2021 | 262.60 Mn |
| Sep 30, 2021 | 233.50 Mn |
Cboe Global Markets EBITDA 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=ebitda&ticker=CBOE&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "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=ebitda&ticker=CBOE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();