Moodys (MCO) EBITDA (2009 - 2026)
Moodys' EBITDA came in at $1.17 billion for Q2 2026, up 24.9% from $938 million a year earlier and up 12.3% from the prior quarter.
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Analysis
Moodys (MCO) EBITDA (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Moodys reported EBITDA of $4.15 billion, up 21.5% 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 Q2 2026 figure represents the highest quarterly EBITDA in data going back to Q1 2009.
- Year-over-year, EBITDA has increased for 13 consecutive quarters, with growth averaging 18.7% over the last eight quarters.
- 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 $1.04 billion (Q1 2026), $894 million (Q4 2025) and $1.04 billion (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | S&P Global | 116.73 Bn | 112.33 Bn | 2.98 Bn | 2.12 Bn |
| 2 | Moodys | 79.69 Bn | 72.12 Bn | 1.67 Bn | 1.17 Bn |
| 3 | Msci | 39.48 Bn | 37.82 Bn | 717.10 Mn | 537.50 Mn |
| 4 | Verisk Analytics | 21.83 Bn | 16.47 Bn | 572.90 Mn | 444.30 Mn |
| 5 | Equifax | 17.14 Bn | 16.54 Bn | 926.40 Mn | 505.60 Mn |
| 6 | TransUnion | 12.68 Bn | 9.66 Bn | - | 418.50 Mn |
| 7 | Factset Research Systems | 9.57 Bn | 8.33 Bn | 310.73 Mn | 212.17 Mn |
| 8 | Morningstar | 7.19 Bn | 5.09 Bn | 423.90 Mn | 214.10 Mn |
| 9 | Mastercard | 494.77 Bn | 454.69 Bn | - | 6.59 Bn |
| 10 | Cme | 94.58 Bn | 94.58 Bn | - | 1.19 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| 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 |
| Sep 30, 2021 | 737.00 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();