Cboe Global Markets (CBOE) Interest Expenses (2010 - 2026)
Cboe Global Markets (CBOE) reported Interest Expenses of $13.2 million for Q2 2026, up 2.3% from $12.9 million a year earlier but down 0.8% from the prior quarter.
Cboe Global Markets (CBOE) Interest Expenses (2010 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Cboe Global Markets' Interest Expenses came in at $53.1 million, up 3.3% year-over-year; for FY2025, it came in at $52.3 million, up 1.6% from FY2024.
- Interest Expenses has a five-year compound annual growth rate of 6.2% (FY2020 to FY2025).
- By year, Interest Expenses came in at $51.5 million in FY2024 (-17.5%), $62.4 million in FY2023 (+4.0%), $60 million in FY2022 (+25.0%) and $48 million in FY2021 (+24.0%).
- Five-year quarterly Interest Expenses spans a low of $11.5 million in Q4 2021 and a high of $17.1 million in Q1 2023.
- Year over year, Interest Expenses has now increased in each of the last five quarters, with an average decline of 0.8% over the last eight quarters.
- The high point for year-over-year Interest Expenses in five years was Q4 2022 (growth of 48.7%); the low point was Q1 2024 (a decline of 24.0%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $13.3 million (Q1 2026), $13.3 million (Q4 2025) and $13.3 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Int Expense (Qtr) |
|---|---|---|---|---|---|
| 1 | Robinhood Markets | 101.14 Bn | 82.23 Bn | - | 159.00 Mn |
| 2 | Bank of New York Mellon | 98.14 Bn | 37.51 Bn | - | 4.49 Bn |
| 3 | Cme | 94.12 Bn | 94.12 Bn | - | 43.60 Mn |
| 4 | Intercontinental Exchange | 85.35 Bn | 79.16 Bn | - | 205.00 Mn |
| 5 | Nasdaq | 51.71 Bn | 49.14 Bn | 1.50 Bn | 86.00 Mn |
| 6 | State Street | 47.94 Bn | 47.94 Bn | - | 1.98 Bn |
| 7 | Interactive Brokers | 38.49 Bn | 31.95 Bn | - | 1.18 Bn |
| 8 | Northern Trust | 30.99 Bn | 30.99 Bn | - | 1.51 Bn |
| 9 | Cboe Global Markets | 28.76 Bn | 20.41 Bn | 731.60 Mn | 13.20 Mn |
| 10 | LPL Financial Holdings | 24.08 Bn | 19.40 Bn | - | 101.50 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 13.20 Mn |
| Mar 31, 2026 | 13.30 Mn |
| Dec 31, 2025 | 13.30 Mn |
| Sep 30, 2025 | 13.30 Mn |
| Jun 30, 2025 | 12.90 Mn |
| Mar 31, 2025 | 12.80 Mn |
| Dec 31, 2024 | 12.90 Mn |
| Sep 30, 2024 | 12.80 Mn |
| Jun 30, 2024 | 12.80 Mn |
| Mar 31, 2024 | 13.00 Mn |
| Dec 31, 2023 | 13.20 Mn |
| Sep 30, 2023 | 15.40 Mn |
| Jun 30, 2023 | 16.70 Mn |
| Mar 31, 2023 | 17.10 Mn |
| Dec 31, 2022 | 17.10 Mn |
| Sep 30, 2022 | 16.10 Mn |
| Jun 30, 2022 | 15.10 Mn |
| Mar 31, 2022 | 11.70 Mn |
| Dec 31, 2021 | 11.50 Mn |
| Sep 30, 2021 | 11.70 Mn |
Cboe Global Markets Interest 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=interest-expenses&ticker=CBOE&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "interest-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=interest-expenses&ticker=CBOE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();