Moodys (MCO) Capital Expenditures (2009 - 2026)
Moodys (MCO) posted Capital Expenditures of $91 million for Q2 2026, up 21.3% from $75 million a year earlier but down 4.2% from the prior quarter.
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Analysis
Moodys (MCO) Capital Expenditures (2009 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Capital Expenditures at Moodys was $352 million, up 15.0% year-over-year; for FY2025, it came in at $326 million, up 2.8% from FY2024.
- Annual Capital Expenditures shows a five-year compound annual growth rate of 25.9% (FY2020 to FY2025).
- In prior years, Moodys' Capital Expenditures was $317 million in FY2024 (+17.0%), $271 million in FY2023 (-4.2%), $283 million in FY2022 (+103.6%) and $139 million in FY2021 (+35.0%).
- Quarterly Capital Expenditures has run from a low of $33 million in Q3 2021 to a high of $95 million in Q1 2026 over five years.
- On a year-over-year basis, Capital Expenditures has increased in each of the last four quarters, with growth averaging 6.6% over the last eight quarters.
- The strongest year-over-year quarter for Capital Expenditures in the past five years was Q1 2022, with growth of 321.4%; the weakest was Q2 2023, with a decline of 27.0%.
- According to Business Quant data, Capital Expenditures for the three prior quarters was $95 million (Q1 2026), $81 million (Q4 2025) and $85 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Capex (Qtr) |
|---|---|---|---|---|---|
| 1 | S&P Global | 116.38 Bn | 111.98 Bn | 2.98 Bn | 38.00 Mn |
| 2 | Moodys | 78.67 Bn | 71.10 Bn | 1.67 Bn | 91.00 Mn |
| 3 | Msci | 39.16 Bn | 37.50 Bn | 717.10 Mn | 11.00 Mn |
| 4 | Verisk Analytics | 21.84 Bn | 16.48 Bn | 572.90 Mn | 68.10 Mn |
| 5 | Equifax | 16.14 Bn | 15.54 Bn | 926.40 Mn | 135.00 Mn |
| 6 | TransUnion | 11.72 Bn | 8.70 Bn | - | 69.20 Mn |
| 7 | Factset Research Systems | 9.66 Bn | 8.43 Bn | 310.73 Mn | 30.48 Mn |
| 8 | Morningstar | 7.13 Bn | 5.03 Bn | 423.90 Mn | 33.20 Mn |
| 9 | Mastercard | 480.27 Bn | 440.19 Bn | - | 291.00 Mn |
| 10 | Cme | 94.12 Bn | 94.12 Bn | - | 23.60 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 91.00 Mn |
| Mar 31, 2026 | 95.00 Mn |
| Dec 31, 2025 | 81.00 Mn |
| Sep 30, 2025 | 85.00 Mn |
| Jun 30, 2025 | 75.00 Mn |
| Mar 31, 2025 | 85.00 Mn |
| Dec 31, 2024 | 74.00 Mn |
| Sep 30, 2024 | 72.00 Mn |
| Jun 30, 2024 | 93.00 Mn |
| Mar 31, 2024 | 78.00 Mn |
| Dec 31, 2023 | 73.00 Mn |
| Sep 30, 2023 | 71.00 Mn |
| Jun 30, 2023 | 54.00 Mn |
| Mar 31, 2023 | 73.00 Mn |
| Dec 31, 2022 | 79.00 Mn |
| Sep 30, 2022 | 71.00 Mn |
| Jun 30, 2022 | 74.00 Mn |
| Mar 31, 2022 | 59.00 Mn |
| Dec 31, 2021 | 62.00 Mn |
| Sep 30, 2021 | 33.00 Mn |
API Access
Moodys Capital Expenditures 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=capital-expenditures&ticker=MCO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "capital-expenditures", "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=capital-expenditures&ticker=MCO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();