Factset Research Systems (FDS) Price to Earnings (2010 - 2026)
Factset Research Systems' (FDS) Price to Earnings came in at 15.52 for fiscal Q3 2026 (quarter ended May 31, 2026), down 52.3% from 32.55 a year earlier but up 14.8% from the prior quarter.
Factset Research Systems (FDS) Price to Earnings (2010 - 2026) Analysis & Trends
For FY2025 (ended Aug 31, 2025), Factset Research Systems' Price to Earnings stood at 23.54, down 21.2% from FY2024.
- Annual Price to Earnings has declined for three consecutive fiscal years.
- In prior fiscal years, Factset Research Systems' Price to Earnings was 29.88 in FY2024 (-15.7%), 35.45 in FY2023 (-14.7%), 41.54 in FY2022 (+16.0%) and 35.79 in FY2021 (+0.2%).
- Quarterly Price to Earnings has run from a low of 13.52 in fiscal Q2 2026 to a high of 43.59 in fiscal Q1 2022 over five years.
- On a year-over-year basis, Price to Earnings has declined in each of the last four quarters, with an average decline of 25.4% over the last eight quarters.
- The strongest year-over-year quarter for Price to Earnings in the past five years was fiscal Q1 2022, with growth of 30.6%; the weakest was fiscal Q2 2026, with a decline of 58.2%.
- According to Business Quant data, Price to Earnings for the three prior fiscal quarters was 13.52 (Q2 2026), 17.22 (Q1 2026) and 23.54 (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | S&P Global | 114.46 Bn | 110.07 Bn | 2.98 Bn |
| 2 | Moodys | 77.50 Bn | 69.93 Bn | 1.67 Bn |
| 3 | Msci | 39.67 Bn | 38.01 Bn | 717.10 Mn |
| 4 | Verisk Analytics | 21.91 Bn | 16.55 Bn | 572.90 Mn |
| 5 | Equifax | 16.44 Bn | 15.84 Bn | 926.40 Mn |
| 6 | TransUnion | 11.91 Bn | 8.89 Bn | - |
| 7 | Factset Research Systems | 9.93 Bn | 8.69 Bn | 310.73 Mn |
| 8 | Morningstar | 7.17 Bn | 5.07 Bn | 423.90 Mn |
| 9 | Mastercard | 479.32 Bn | 439.24 Bn | - |
| 10 | Cme | 95.24 Bn | 95.24 Bn | - |
Historic Data
| Date | Value |
|---|---|
| May 31, 2026 | 15.52 |
| Feb 28, 2026 | 13.52 |
| Nov 30, 2025 | 17.22 |
| Aug 31, 2025 | 23.54 |
| May 31, 2025 | 32.55 |
| Feb 28, 2025 | 32.33 |
| Nov 30, 2024 | 34.66 |
| Aug 31, 2024 | 29.88 |
| May 31, 2024 | 30.01 |
| Feb 29, 2024 | 36.04 |
| Nov 30, 2023 | 35.96 |
| Aug 31, 2023 | 35.45 |
| May 31, 2023 | 28.98 |
| Feb 28, 2023 | 35.47 |
| Nov 30, 2022 | 41.37 |
| Aug 31, 2022 | 41.54 |
| May 31, 2022 | 36.84 |
| Feb 28, 2022 | 36.69 |
| Nov 30, 2021 | 43.59 |
| Aug 31, 2021 | 35.79 |
Factset Research Systems Price to Earnings 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=price-to-earnings&ticker=FDS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "price-to-earnings", "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=price-to-earnings&ticker=FDS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();