Factset Research Systems (FDS) EPS (Diluted) (2009 - 2026)
Factset Research Systems (FDS) reported EPS (Diluted) of $3.50 for fiscal Q3 2026 (quarter ended May 31, 2026), down 9.6% from $3.87 a year earlier and down 2.5% from the prior quarter.
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Analysis
Factset Research Systems (FDS) EPS (Diluted) (2009 - 2026) Analysis & Trends
Over the twelve months ended May 31, 2026, Factset Research Systems' EPS (Diluted) came in at $15.64, up 12.5% year-over-year; for FY2025 (ended Aug 31, 2025), it came in at $15.55, up 11.8% from FY2024.
- EPS (Diluted) has increased for three consecutive fiscal years, with a five-year compound annual growth rate of 10.0% (FY2020 to FY2025).
- By fiscal year, EPS (Diluted) came in at $13.91 in FY2024 (+15.6%), $12.04 in FY2023 (+17.5%), $10.25 in FY2022 (-1.1%) and $10.36 in FY2021 (+7.4%).
- The fiscal Q3 2026 figure ranks as the lowest quarterly EPS (Diluted) since fiscal Q4 2024.
- Year over year, EPS (Diluted) gained in five of the last eight quarters, with growth averaging 12.5%.
- The high point for year-over-year EPS (Diluted) in five years was fiscal Q3 2023 (growth of 78.9%); the low point was fiscal Q4 2023 (a decline of 37.9%).
- Per Business Quant data, the three fiscal quarters before Q3 2026 came in at $3.59 (Q2 2026), $4.06 (Q1 2026) and $4.00 (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EPS (Diluted) (Qtr) |
|---|---|---|---|---|---|
| 1 | S&P Global | 116.38 Bn | 111.98 Bn | 2.98 Bn | 4.12 |
| 2 | Moodys | 78.67 Bn | 71.10 Bn | 1.67 Bn | 5.03 |
| 3 | Msci | 39.16 Bn | 37.50 Bn | 717.10 Mn | 4.69 |
| 4 | Verisk Analytics | 21.84 Bn | 16.48 Bn | 572.90 Mn | 1.75 |
| 5 | Equifax | 16.14 Bn | 15.54 Bn | 926.40 Mn | 1.54 |
| 6 | TransUnion | 11.72 Bn | 8.70 Bn | - | 0.74 |
| 7 | Factset Research Systems | 9.66 Bn | 8.43 Bn | 310.73 Mn | 3.50 |
| 8 | Morningstar | 7.13 Bn | 5.03 Bn | 423.90 Mn | 2.83 |
| 9 | Mastercard | 480.27 Bn | 440.19 Bn | - | 4.97 |
| 10 | Cme | 94.12 Bn | 94.12 Bn | - | 2.88 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| May 31, 2026 | 3.50 |
| Feb 28, 2026 | 3.59 |
| Nov 30, 2025 | 4.06 |
| Aug 31, 2025 | 4.00 |
| May 31, 2025 | 3.87 |
| Feb 28, 2025 | 3.76 |
| Nov 30, 2024 | 3.89 |
| Aug 31, 2024 | 2.32 |
| May 31, 2024 | 4.09 |
| Feb 29, 2024 | 3.65 |
| Nov 30, 2023 | 3.84 |
| Aug 31, 2023 | 1.67 |
| May 31, 2023 | 3.46 |
| Feb 28, 2023 | 3.38 |
| Nov 30, 2022 | 3.52 |
| Aug 31, 2022 | 2.70 |
| May 31, 2022 | 1.93 |
| Feb 28, 2022 | 2.84 |
| Nov 30, 2021 | 2.79 |
| Aug 31, 2021 | 2.62 |
API Access
Factset Research Systems EPS (Diluted) 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=eps-diluted&ticker=FDS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "eps-diluted", "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=eps-diluted&ticker=FDS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();