Moodys (MCO) EPS (Diluted) (2009 - 2026)
Moodys (MCO) reported EPS (Diluted) of $4.24 for Q3 2026, up 17.8% from $3.60 a year earlier but down 15.8% from the prior quarter.
Moodys (MCO) EPS (Diluted) (2009 - 2026) Analysis & Trends
Over the twelve months ended Sep 30, 2026, Moodys' EPS (Diluted) came in at $16.64, up 33.1% year-over-year; for FY2025, it came in at $13.67, up 21.3% from FY2024.
- EPS (Diluted) has increased for three consecutive years, with a five-year compound annual growth rate of 7.8% (FY2020 to FY2025).
- By year, EPS (Diluted) came in at $11.26 in FY2024 (+29.0%), $8.73 in FY2023 (+17.4%), $7.44 in FY2022 (-36.9%) and $11.78 in FY2021 (+25.4%).
- Five-year quarterly EPS (Diluted) spans a low of $1.33 in Q4 2022 and a high of $5.03 in Q2 2026.
- Year over year, EPS (Diluted) has now increased in each of the last 15 quarters, with growth averaging 24.4% over the last eight quarters.
- The high point for year-over-year EPS (Diluted) in five years was Q2 2026 (growth of 56.9%); the low point was Q2 2022 (a decline of 42.4%).
- Per Business Quant data, the three quarters before Q3 2026 came in at $5.03 (Q2 2026), $3.73 (Q1 2026) and $3.39 (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EPS (Diluted) (Qtr) |
|---|---|---|---|---|---|
| 1 | Msci | 235.55 Bn | 234.03 Bn | 739.80 Mn | 0.97 |
| 2 | S&P Global | 137.22 Bn | 132.42 Bn | 2.64 Bn | 4.25 |
| 3 | Moodys | 88.04 Bn | 81.11 Bn | 1.50 Bn | 4.24 |
| 4 | Verisk Analytics | 26.17 Bn | 22.36 Bn | 567.00 Mn | 1.70 |
| 5 | Equifax | 22.05 Bn | 21.44 Bn | 940.10 Mn | 1.79 |
| 6 | TransUnion | 15.64 Bn | 12.48 Bn | - | 0.81 |
| 7 | Factset Research Systems | 11.49 Bn | 10.35 Bn | 308.40 Mn | 3.31 |
| 8 | Morningstar | 9.15 Bn | 7.04 Bn | 431.40 Mn | 3.04 |
| 9 | Mastercard | 570.55 Bn | 530.63 Bn | - | 5.28 |
| 10 | Cme | 110.48 Bn | 98.81 Bn | 359.20 Mn | 2.89 |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 4.24 |
| Jun 30, 2026 | 5.03 |
| Mar 31, 2026 | 3.73 |
| Dec 31, 2025 | 3.39 |
| Sep 30, 2025 | 3.60 |
| Jun 30, 2025 | 3.21 |
| Mar 31, 2025 | 3.46 |
| Dec 31, 2024 | 2.16 |
| Sep 30, 2024 | 2.93 |
| Jun 30, 2024 | 3.02 |
| Mar 31, 2024 | 3.15 |
| Dec 31, 2023 | 1.85 |
| Sep 30, 2023 | 2.11 |
| Jun 30, 2023 | 2.05 |
| Mar 31, 2023 | 2.72 |
| Dec 31, 2022 | 1.33 |
| Sep 30, 2022 | 1.65 |
| Jun 30, 2022 | 1.77 |
| Mar 31, 2022 | 2.68 |
| Dec 31, 2021 | 2.27 |
Moodys 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=MCO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "eps-diluted", "ticker": "MCO", "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=MCO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();