Cboe Global Markets (CBOE) Tax Provisions (2010 - 2026)
Cboe Global Markets' Tax Provisions was $126.3 million in Q3 2026, down 2.3% from $129.3 million a year earlier and down 10.8% from the prior quarter.
Cboe Global Markets (CBOE) Tax Provisions (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Cboe Global Markets' Tax Provisions was $535.9 million through Sep 30, 2026, up 30.2% year-over-year; for FY2025, it was $466.6 million, up 46.3% from FY2024.
- Tax Provisions has now increased for three consecutive years, with a five-year compound annual growth rate of 19.4% (FY2020 to FY2025).
- In earlier years, Tax Provisions was $318.9 million in FY2024 (+11.4%), $286.2 million in FY2023 (+44.6%), $197.9 million in FY2022 (-12.9%) and $227.1 million in FY2021 (+18.2%).
- The Q3 2026 figure marks the lowest quarterly Tax Provisions since Q2 2025.
- Compared with a year earlier, Tax Provisions was higher in seven of the last eight quarters, with growth averaging 33.6%.
- The best year-over-year quarter for Tax Provisions over five years was Q1 2022 (growth of 107.0%); the worst was Q1 2023 (a decline of 35.1%).
- Per Business Quant data, CBOE's Tax Provisions in the three quarters before Q3 2026 was $141.6 million (Q2 2026), $129.8 million (Q1 2026) and $138.2 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Taxes (Qtr) |
|---|---|---|---|---|---|
| 1 | Cme | 109.34 Bn | 97.67 Bn | - | 317.90 Mn |
| 2 | Bank of New York Mellon | 103.32 Bn | 36.94 Bn | - | 499.00 Mn |
| 3 | Intercontinental Exchange | 97.84 Bn | 90.74 Bn | - | 286.00 Mn |
| 4 | Robinhood Markets | 73.91 Bn | 53.45 Bn | - | 149.00 Mn |
| 5 | Nasdaq | 60.30 Bn | 57.74 Bn | 1.48 Bn | 162.00 Mn |
| 6 | State Street | 47.09 Bn | 47.09 Bn | - | 298.00 Mn |
| 7 | Cboe Global Markets | 37.14 Bn | 27.62 Bn | 712.20 Mn | 126.30 Mn |
| 8 | Interactive Brokers | 35.28 Bn | 11.58 Bn | - | 148.00 Mn |
| 9 | Northern Trust | 32.35 Bn | 32.35 Bn | - | 153.60 Mn |
| 10 | Tradeweb Markets | 26.89 Bn | 18.69 Bn | - | 65.10 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 126.30 Mn |
| Jun 30, 2026 | 141.60 Mn |
| Mar 31, 2026 | 129.80 Mn |
| Dec 31, 2025 | 138.20 Mn |
| Sep 30, 2025 | 129.30 Mn |
| Jun 30, 2025 | 99.50 Mn |
| Mar 31, 2025 | 99.60 Mn |
| Dec 31, 2024 | 83.20 Mn |
| Sep 30, 2024 | 90.50 Mn |
| Jun 30, 2024 | 62.60 Mn |
| Mar 31, 2024 | 82.60 Mn |
| Dec 31, 2023 | 75.50 Mn |
| Sep 30, 2023 | 61.90 Mn |
| Jun 30, 2023 | 74.00 Mn |
| Mar 31, 2023 | 74.80 Mn |
| Dec 31, 2022 | 76.10 Mn |
| Sep 30, 2022 | 78.80 Mn |
| Jun 30, 2022 | -72.30 Mn |
| Mar 31, 2022 | 115.30 Mn |
| Dec 31, 2021 | 44.30 Mn |
Cboe Global Markets Tax Provisions 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=tax-provisions&ticker=CBOE&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "tax-provisions", "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=tax-provisions&ticker=CBOE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();