Factset Research Systems (FDS) EV to EBITDA (2010 - 2026)
Factset Research Systems' EV to EBITDA came in at 9.45 for fiscal Q3 2026 (quarter ended May 31, 2026), down 52.8% from 20.03 a year earlier but up 13.5% from the prior quarter.
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Analysis
Factset Research Systems (FDS) EV to EBITDA (2010 - 2026) Analysis & Trends
Over the trailing twelve months to May 31, 2026, Factset Research Systems reported EV to EBITDA of 8.41, down 55.0% year-over-year; for FY2025 (ended Aug 31, 2025), it was 15.12, down 19.7% from FY2024.
- EV to EBITDA has declined in each of the last three fiscal years.
- Going back by fiscal year, EV to EBITDA was 18.82 in FY2024 (-14.3%), 21.97 in FY2023 (-22.6%), 28.37 in FY2022 (+12.5%) and 25.23 in FY2021 (-1.4%).
- The five-year range for quarterly EV to EBITDA is 8.33 (fiscal Q2 2026) to 31.34 (fiscal Q1 2022).
- Year-over-year, EV to EBITDA has declined for four consecutive quarters, with an average decline of 24.7% over the last eight quarters.
- The fastest year-over-year change in EV to EBITDA over five years came in fiscal Q1 2022 (growth of 31.0%), and the weakest in fiscal Q2 2026 (a decline of 59.1%).
- Business Quant data shows FDS's EV to EBITDA at 8.33 (Q2 2026), 10.96 (Q1 2026) and 15.12 (Q4 2025) in the three fiscal quarters before Q3 2026.
Peer Set
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
Download Data
Historic Data
| Date | Value |
|---|---|
| May 31, 2026 | 9.45 |
| Feb 28, 2026 | 8.33 |
| Nov 30, 2025 | 10.96 |
| Aug 31, 2025 | 15.12 |
| May 31, 2025 | 20.03 |
| Feb 28, 2025 | 20.35 |
| Nov 30, 2024 | 21.87 |
| Aug 31, 2024 | 18.82 |
| May 31, 2024 | 18.41 |
| Feb 29, 2024 | 22.29 |
| Nov 30, 2023 | 22.34 |
| Aug 31, 2023 | 21.97 |
| May 31, 2023 | 18.90 |
| Feb 28, 2023 | 22.77 |
| Nov 30, 2022 | 27.67 |
| Aug 31, 2022 | 28.37 |
| May 31, 2022 | 25.86 |
| Feb 28, 2022 | 26.54 |
| Nov 30, 2021 | 31.34 |
| Aug 31, 2021 | 25.23 |
API Access
Factset Research Systems EV to EBITDA 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=ev-to-ebitda&ticker=FDS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ev-to-ebitda", "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=ev-to-ebitda&ticker=FDS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();