Cboe Global Markets (CBOE) Return on Sales [ROS] (2010 - 2026)
Cboe Global Markets (CBOE) posted Return on Sales [ROS] of 32.99% for Q2 2026, up 4.09 percentage points from 28.90% a year earlier but down 6.73 percentage points from the prior quarter.
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Analysis
Cboe Global Markets (CBOE) Return on Sales [ROS] (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Return on Sales [ROS] at Cboe Global Markets was 34.69%, up 6.03 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 six quarters, with an average year-over-year change of +3.43 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 39.72% (Q1 2026), 33.54% (Q4 2025) and 32.43% (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | Robinhood Markets | 101.35 Bn | 82.45 Bn | - | 66.36% |
| 2 | Bank of New York Mellon | 98.65 Bn | 38.02 Bn | - | 119.30% |
| 3 | Cme | 94.54 Bn | 94.54 Bn | - | 64.89% |
| 4 | Intercontinental Exchange | 84.23 Bn | 78.04 Bn | - | 38.52% |
| 5 | Nasdaq | 50.77 Bn | 48.20 Bn | 1.50 Bn | 28.12% |
| 6 | State Street | 48.31 Bn | 48.31 Bn | - | 83.30% |
| 7 | Interactive Brokers | 39.79 Bn | 33.24 Bn | - | 138.98% |
| 8 | Northern Trust | 31.37 Bn | 31.37 Bn | - | 191.07% |
| 9 | Cboe Global Markets | 28.34 Bn | 20.00 Bn | 731.60 Mn | 32.99% |
| 10 | LPL Financial Holdings | 24.92 Bn | 20.24 Bn | - | 11.90% |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| 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% |
| Sep 30, 2021 | 23.35% |
API Access
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_KEYimport 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();