Factset Research Systems (FDS) Enterprise Value (2009 - 2026)
Factset Research Systems (FDS) recorded Enterprise Value of $8.48 billion in fiscal Q3 2026 (quarter ended May 31, 2026), down 50.1% from $16.99 billion a year earlier but up 10.7% from the prior quarter.
Factset Research Systems (FDS) Enterprise Value (2009 - 2026) Analysis & Trends
On a TTM basis, Factset Research Systems' Enterprise Value came in at $7.55 billion as of May 31, 2026, down 52.4% year-over-year; for FY2025 (ended Aug 31, 2025), it was $13.7 billion, down 11.9% from FY2024.
- Annual Enterprise Value has a five-year compound annual growth rate of 1.5% (FY2020 to FY2025).
- Across earlier fiscal years, Enterprise Value came in at $15.56 billion in FY2024 (-3.6%), $16.14 billion in FY2023 (+1.2%), $15.95 billion in FY2022 (+17.4%) and $13.58 billion in FY2021 (+6.8%).
- Quarterly Enterprise Value has ranged from $7.66 billion in fiscal Q2 2026 to $18.31 billion in fiscal Q1 2025 over the past five years.
- On a year-over-year basis, Enterprise Value has declined for four consecutive quarters, with an average decline of 17.9% over the last eight quarters.
- Peak year-over-year performance for Enterprise Value in the last five years was growth of 40.3% in fiscal Q1 2022, against a decline of 55.6% in fiscal Q2 2026 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $7.66 billion (Q2 2026), $10.03 billion (Q1 2026) and $13.7 billion (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | S&P Global | 115.73 Bn | 111.34 Bn | 2.98 Bn |
| 2 | Moodys | 78.77 Bn | 71.20 Bn | 1.67 Bn |
| 3 | Msci | 39.23 Bn | 37.58 Bn | 717.10 Mn |
| 4 | Verisk Analytics | 21.59 Bn | 16.23 Bn | 572.90 Mn |
| 5 | Equifax | 16.56 Bn | 15.96 Bn | 926.40 Mn |
| 6 | TransUnion | 12.32 Bn | 9.30 Bn | - |
| 7 | Factset Research Systems | 9.30 Bn | 8.06 Bn | 310.73 Mn |
| 8 | Morningstar | 6.99 Bn | 4.89 Bn | 423.90 Mn |
| 9 | Mastercard | 490.78 Bn | 450.70 Bn | - |
| 10 | Cme | 94.57 Bn | 94.57 Bn | - |
Historic Data
| Date | Value |
|---|---|
| May 31, 2026 | 8.48 Bn |
| Feb 28, 2026 | 7.66 Bn |
| Nov 30, 2025 | 10.03 Bn |
| Aug 31, 2025 | 13.70 Bn |
| May 31, 2025 | 16.99 Bn |
| Feb 28, 2025 | 17.26 Bn |
| Nov 30, 2024 | 18.31 Bn |
| Aug 31, 2024 | 15.56 Bn |
| May 31, 2024 | 14.87 Bn |
| Feb 29, 2024 | 17.18 Bn |
| Nov 30, 2023 | 16.81 Bn |
| Aug 31, 2023 | 16.14 Bn |
| May 31, 2023 | 14.19 Bn |
| Feb 28, 2023 | 15.41 Bn |
| Nov 30, 2022 | 17.16 Bn |
| Aug 31, 2022 | 15.95 Bn |
| May 31, 2022 | 13.94 Bn |
| Feb 28, 2022 | 14.58 Bn |
| Nov 30, 2021 | 16.99 Bn |
| Aug 31, 2021 | 13.58 Bn |
Factset Research Systems Enterprise Value 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=enterprise-value&ticker=FDS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "enterprise-value", "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=enterprise-value&ticker=FDS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();