Moodys (MCO) EBITDA (2009 - 2026)
Moodys' EBITDA came in at $1.03 billion for Q3 2026, down 1.0% from $1.04 billion a year earlier and down 12.1% from the prior quarter.
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Analysis
Moodys (MCO) EBITDA (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Sep 30, 2026, Moodys reported EBITDA of $4.14 billion, up 14.6% year-over-year; for FY2025, it was $3.83 billion, up 15.9% from FY2024.
- EBITDA has increased in each of the last three years, with a five-year compound annual growth rate of 8.0% (FY2020 to FY2025).
- Going back by year, EBITDA was $3.31 billion in FY2024 (+31.7%), $2.51 billion in FY2023 (+13.4%), $2.21 billion in FY2022 (-28.6%) and $3.1 billion in FY2021 (+18.9%).
- The five-year range for quarterly EBITDA is $395 million (Q4 2022) to $1.17 billion (Q2 2026).
- Year-over-year, EBITDA increased in seven of the last eight quarters, with growth averaging 14.3%.
- The fastest year-over-year change in EBITDA over five years came in Q4 2023 (growth of 50.6%), and the weakest in Q4 2022 (a decline of 33.2%).
- Business Quant data shows MCO's EBITDA at $1.17 billion (Q2 2026), $1.04 billion (Q1 2026) and $894 million (Q4 2025) in the three quarters before Q3 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | S&P Global | 135.95 Bn | 125.80 Bn | 2.64 Bn | 2.18 Bn |
| 2 | Moodys | 87.18 Bn | 80.11 Bn | 1.50 Bn | 1.03 Bn |
| 3 | Msci | 46.24 Bn | 44.72 Bn | 739.80 Mn | 555.70 Mn |
| 4 | Verisk Analytics | 26.46 Bn | 21.10 Bn | 572.90 Mn | 445.40 Mn |
| 5 | Equifax | 22.29 Bn | 21.56 Bn | 940.10 Mn | 551.70 Mn |
| 6 | TransUnion | 15.65 Bn | 12.34 Bn | - | 431.20 Mn |
| 7 | Factset Research Systems | 11.79 Bn | 10.64 Bn | 308.40 Mn | 203.75 Mn |
| 8 | Morningstar | 9.04 Bn | 6.93 Bn | 431.40 Mn | 220.50 Mn |
| 9 | Mastercard | 577.18 Bn | 537.27 Bn | - | 6.91 Bn |
| 10 | Cme | 108.04 Bn | 96.37 Bn | - | 1.22 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 1.03 Bn |
| Jun 30, 2026 | 1.17 Bn |
| Mar 31, 2026 | 1.04 Bn |
| Dec 31, 2025 | 894.00 Mn |
| Sep 30, 2025 | 1.04 Bn |
| Jun 30, 2025 | 938.00 Mn |
| Mar 31, 2025 | 959.00 Mn |
| Dec 31, 2024 | 674.00 Mn |
| Sep 30, 2024 | 846.00 Mn |
| Jun 30, 2024 | 885.00 Mn |
| Mar 31, 2024 | 901.00 Mn |
| Dec 31, 2023 | 595.00 Mn |
| Sep 30, 2023 | 630.00 Mn |
| Jun 30, 2023 | 643.00 Mn |
| Mar 31, 2023 | 642.00 Mn |
| Dec 31, 2022 | 395.00 Mn |
| Sep 30, 2022 | 496.00 Mn |
| Jun 30, 2022 | 589.00 Mn |
| Mar 31, 2022 | 734.00 Mn |
| Dec 31, 2021 | 591.00 Mn |
API Access
Moodys 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=ebitda&ticker=MCO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "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=ebitda&ticker=MCO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();