Moodys (MCO) Exchange Rate Effect (2009 - 2026)
Moodys' Exchange Rate Effect came in at $5 million for Q3 2026, compared with -$8 million a year earlier and down 70.6% from the prior quarter.
Moodys (MCO) Exchange Rate Effect (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Sep 30, 2026, Moodys reported Exchange Rate Effect of -$26 million; for FY2025, it came in at $136 million.
- Exchange Rate Effect carries a five-year compound annual growth rate of 23.7% (FY2020 to FY2025).
- Going back by year, Exchange Rate Effect was -$58 million in FY2024, $41 million in FY2023, -$46 million in FY2022 and -$50 million in FY2021.
- The five-year range for quarterly Exchange Rate Effect is -$93 million (Q4 2024) to $100 million (Q2 2025).
- Business Quant data shows MCO's Exchange Rate Effect at $17 million (Q2 2026), -$44 million (Q1 2026) and -$4 million (Q4 2025) in the three quarters before Q3 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | FX Effect (Qtr) |
|---|---|---|---|---|---|
| 1 | Msci | 236.00 Bn | 234.48 Bn | 739.80 Mn | -100,000.00 |
| 2 | S&P Global | 137.30 Bn | 132.50 Bn | 2.64 Bn | 3.00 Mn |
| 3 | Moodys | 87.63 Bn | 80.69 Bn | 1.50 Bn | 5.00 Mn |
| 4 | Verisk Analytics | 26.66 Bn | 22.85 Bn | 567.00 Mn | -400,000.00 |
| 5 | Equifax | 22.03 Bn | 21.43 Bn | 940.10 Mn | -800,000.00 |
| 6 | TransUnion | 15.46 Bn | 12.30 Bn | - | -6.70 Mn |
| 7 | Factset Research Systems | 11.73 Bn | 10.58 Bn | 308.40 Mn | -631,000.00 |
| 8 | Morningstar | 9.14 Bn | 7.03 Bn | 431.40 Mn | 500,000.00 |
| 9 | Mastercard | 572.29 Bn | 532.37 Bn | - | -11.00 Mn |
| 10 | Cme | 113.65 Bn | 101.99 Bn | 359.20 Mn | - |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 5.00 Mn |
| Jun 30, 2026 | 17.00 Mn |
| Mar 31, 2026 | -44.00 Mn |
| Dec 31, 2025 | -4.00 Mn |
| Sep 30, 2025 | -8.00 Mn |
| Jun 30, 2025 | 100.00 Mn |
| Mar 31, 2025 | 48.00 Mn |
| Dec 31, 2024 | -93.00 Mn |
| Sep 30, 2024 | 69.00 Mn |
| Jun 30, 2024 | -9.00 Mn |
| Mar 31, 2024 | -25.00 Mn |
| Dec 31, 2023 | 54.00 Mn |
| Sep 30, 2023 | -37.00 Mn |
| Jun 30, 2023 | 3.00 Mn |
| Mar 31, 2023 | 21.00 Mn |
| Dec 31, 2022 | 77.00 Mn |
| Sep 30, 2022 | -52.00 Mn |
| Jun 30, 2022 | -53.00 Mn |
| Mar 31, 2022 | -18.00 Mn |
| Dec 31, 2021 | -12.00 Mn |
Moodys Exchange Rate Effect 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=exchange-rate-effect&ticker=MCO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "exchange-rate-effect", "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=exchange-rate-effect&ticker=MCO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();