Cboe Global Markets (CBOE) Return on Sales [ROS] (2010 - 2026)
Cboe Global Markets (CBOE) posted Return on Sales [ROS] of 39.32% for Q3 2026, up 6.89 percentage points from 32.43% a year earlier and up 6.33 percentage points from the prior quarter.
Cboe Global Markets (CBOE) Return on Sales [ROS] (2010 - 2026) Analysis & Trends
For the trailing twelve months through Sep 30, 2026, Return on Sales [ROS] at Cboe Global Markets was 36.37%, up 6.88 percentage points year-over-year; for FY2025, it came in at 31.12%, up 4.29 percentage points from FY2024.
- Annual Return on Sales [ROS] shows a five-year change of +11.80 percentage points (FY2020 to FY2025).
- In prior years, Cboe Global Markets' Return on Sales [ROS] was 26.83% in FY2024 (-1.21 pp), 28.03% in FY2023 (+15.67 pp), 12.37% in FY2022 (-10.69 pp) and 23.06% in FY2021 (+3.74 pp).
- Quarterly Return on Sales [ROS] has run from a low of -24.08% in Q2 2022 to a high of 39.72% in Q1 2026 over five years.
- On a year-over-year basis, Return on Sales [ROS] has increased in each of the last seven quarters, with an average year-over-year change of +4.38 percentage points over the last eight quarters.
- The strongest year-over-year quarter for Return on Sales [ROS] in the past five years was Q2 2023, with a gain of 51.05 percentage points; the weakest was Q2 2022, with a drop of 47.81 percentage points.
- According to Business Quant data, Return on Sales [ROS] for the three prior quarters was 32.99% (Q2 2026), 39.72% (Q1 2026) and 33.54% (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | Cme | 108.95 Bn | 97.29 Bn | - | 65.70% |
| 2 | Bank of New York Mellon | 102.82 Bn | 36.44 Bn | - | 113.77% |
| 3 | Intercontinental Exchange | 98.21 Bn | 91.10 Bn | - | 38.84% |
| 4 | Robinhood Markets | 74.92 Bn | 54.46 Bn | - | 58.57% |
| 5 | Nasdaq | 60.69 Bn | 58.13 Bn | 1.48 Bn | 30.59% |
| 6 | State Street | 46.98 Bn | 46.98 Bn | - | 85.91% |
| 7 | Cboe Global Markets | 36.89 Bn | 27.37 Bn | 712.20 Mn | 39.32% |
| 8 | Interactive Brokers | 35.15 Bn | 11.46 Bn | - | 144.98% |
| 9 | Northern Trust | 32.35 Bn | 32.35 Bn | - | 160.10% |
| 10 | Tradeweb Markets | 27.24 Bn | 19.05 Bn | - | 43.36% |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 39.32% |
| Jun 30, 2026 | 32.99% |
| Mar 31, 2026 | 39.72% |
| Dec 31, 2025 | 33.54% |
| Sep 30, 2025 | 32.43% |
| Jun 30, 2025 | 28.90% |
| Mar 31, 2025 | 29.62% |
| Dec 31, 2024 | 26.95% |
| Sep 30, 2024 | 29.12% |
| Jun 30, 2024 | 21.57% |
| Mar 31, 2024 | 29.50% |
| Dec 31, 2023 | 30.35% |
| Sep 30, 2023 | 29.84% |
| Jun 30, 2023 | 26.97% |
| Mar 31, 2023 | 25.09% |
| Dec 31, 2022 | 24.93% |
| Sep 30, 2022 | 23.83% |
| Jun 30, 2022 | -24.08% |
| Mar 31, 2022 | 24.60% |
| Dec 31, 2021 | 25.46% |
Cboe Global Markets Return on Sales [ROS] 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=return-on-sales-%5Bros%5D&ticker=CBOE&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "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=return-on-sales-%5Bros%5D&ticker=CBOE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();