Factset Research Systems (FDS) Shares Outstanding (2009 - 2026)
Factset Research Systems' Shares Outstanding came in at 36.12 million for fiscal Q3 2026 (quarter ended May 31, 2026), down 4.7% from 37.91 million a year earlier and down 2.2% from the prior quarter.
Powered by 
Analysis
Factset Research Systems (FDS) Shares Outstanding (2009 - 2026) Analysis & Trends
For FY2025 (ended Aug 31, 2025), Factset Research Systems' Shares Outstanding was 37.92 million, down 0.4% from FY2024.
- Shares Outstanding carries a five-year compound annual growth rate of 0.0% (FY2020 to FY2025).
- Going back by fiscal year, Shares Outstanding was 38.06 million in FY2024 (-0.4%), 38.19 million in FY2023 (+0.9%), 37.86 million in FY2022 (unchanged) and 37.86 million in FY2021 (-0.2%).
- The fiscal Q3 2026 figure represents the lowest quarterly Shares Outstanding in data going back to fiscal Q1 2010.
- Year-over-year, Shares Outstanding has declined for six consecutive quarters, with an average decline of 1.3% over the last eight quarters.
- The fastest year-over-year change in Shares Outstanding over five years came in fiscal Q1 2023 (growth of 1.2%), and the weakest in fiscal Q3 2026 (a decline of 4.7%).
- Business Quant data shows FDS's Shares Outstanding at 36.93 million (Q2 2026), 37.41 million (Q1 2026) and 37.92 million (Q4 2025) in the three fiscal quarters before Q3 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Shares Outstanding (Qtr) |
|---|---|---|---|---|---|
| 1 | S&P Global | 116.38 Bn | 111.98 Bn | 2.98 Bn | 295.40 Mn |
| 2 | Moodys | 78.67 Bn | 71.10 Bn | 1.67 Bn | 174.10 Mn |
| 3 | Msci | 39.16 Bn | 37.50 Bn | 717.10 Mn | 72.80 Mn |
| 4 | Verisk Analytics | 21.84 Bn | 16.48 Bn | 572.90 Mn | 130.76 Mn |
| 5 | Equifax | 16.14 Bn | 15.54 Bn | 926.40 Mn | 118.40 Mn |
| 6 | TransUnion | 11.72 Bn | 8.70 Bn | - | 192.30 Mn |
| 7 | Factset Research Systems | 9.66 Bn | 8.43 Bn | 310.73 Mn | 36.12 Mn |
| 8 | Morningstar | 7.13 Bn | 5.03 Bn | 423.90 Mn | 37.80 Mn |
| 9 | Mastercard | 480.27 Bn | 440.19 Bn | - | 882.00 Mn |
| 10 | Cme | 94.12 Bn | 94.12 Bn | - | 360.68 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| May 31, 2026 | 36.12 Mn |
| Feb 28, 2026 | 36.93 Mn |
| Nov 30, 2025 | 37.41 Mn |
| Aug 31, 2025 | 37.92 Mn |
| May 31, 2025 | 37.91 Mn |
| Feb 28, 2025 | 38.02 Mn |
| Nov 30, 2024 | 38.01 Mn |
| Aug 31, 2024 | 38.06 Mn |
| May 31, 2024 | 38.09 Mn |
| Feb 29, 2024 | 38.10 Mn |
| Nov 30, 2023 | 38.02 Mn |
| Aug 31, 2023 | 38.19 Mn |
| May 31, 2023 | 38.28 Mn |
| Feb 28, 2023 | 38.28 Mn |
| Nov 30, 2022 | 38.12 Mn |
| Aug 31, 2022 | 37.86 Mn |
| May 31, 2022 | 37.93 Mn |
| Feb 28, 2022 | 37.84 Mn |
| Nov 30, 2021 | 37.68 Mn |
| Aug 31, 2021 | 37.86 Mn |
API Access
Factset Research Systems Shares Outstanding 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=shares-outstanding&ticker=FDS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "shares-outstanding", "ticker": "FDS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=shares-outstanding&ticker=FDS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();