Wheaton Precious Metals (WPM) Operating Leases (2019 - 2026)
Wheaton Precious Metals' Operating Leases was $1.97 billion in the quarter ended Jun 30, 2026, compared with $5.32 million a year earlier.
Wheaton Precious Metals (WPM) Operating Leases (2019 - 2026) Analysis & Trends
As of Dec 31, 2025, Operating Leases at Wheaton Precious Metals came in at $7.33 million, up 49.3% from the prior year.
- Operating Leases shows a five-year compound annual growth rate of 20.7% (years ended Dec 2020 to Dec 2025).
- In earlier years, Operating Leases was $4.91 million in the year ended Dec 31, 2024 (-12.7%), $5.63 million in the year ended Dec 31, 2023 (+388.3%), $1.15 million in the year ended Dec 31, 2022 (-44.1%) and $2.06 million in the year ended Dec 31, 2021 (-28.1%).
- The figure for the quarter ended Jun 30, 2026 marks the highest quarterly Operating Leases in data going back to the quarter ended Dec 31, 2009.
- Compared with a year earlier, Operating Leases was higher in four of the last seven quarters, with growth averaging 14.8%.
- The best year-over-year quarter for Operating Leases over five years was the quarter ended Mar 31, 2024 (growth of 476.3%); the worst was the quarter ended Mar 31, 2023 (a decline of 49.6%).
- Per Business Quant data, WPM's Operating Leases in the three quarters before the quarter ended Jun 30, 2026 was $7.08 million (quarter ended Mar 31, 2026), $7.33 million (quarter ended Dec 31, 2025) and $7.42 million (quarter ended Sep 30, 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | BlackRock | 175.82 Bn | 121.95 Bn | - |
| 2 | Spdr Gold Trust | 136.93 Bn | -421.07 Bn | - |
| 3 | Blackstone | 87.73 Bn | 77.71 Bn | - |
| 4 | Brookfield | 83.99 Bn | -99.33 Bn | - |
| 5 | Kkr | 80.54 Bn | 681.40 Mn | - |
| 6 | Brookfield Asset Management | 73.47 Bn | 68.27 Bn | - |
| 7 | Apollo Global Management | 66.53 Bn | -16.26 Bn | 10.56 Bn |
| 8 | Wheaton Precious Metals | 59.78 Bn | 55.21 Bn | 687.86 Mn |
| 9 | Franco Nevada | 46.66 Bn | 44.02 Bn | 451.00 Mn |
| 10 | Ameriprise Financial | 44.98 Bn | 6.40 Bn | 4.72 Bn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 6.88 Mn |
| Mar 31, 2026 | 7.08 Mn |
| Dec 31, 2025 | 7.33 Mn |
| Sep 30, 2025 | 7.42 Mn |
| Jun 30, 2025 | 7.68 Mn |
| Mar 31, 2025 | 7.60 Mn |
| Dec 31, 2024 | 4.91 Mn |
| Sep 30, 2024 | 5.34 Mn |
| Jun 30, 2024 | 5.30 Mn |
| Mar 31, 2024 | 5.42 Mn |
| Dec 31, 2023 | 5.63 Mn |
| Sep 30, 2023 | 5.65 Mn |
| Jun 30, 2023 | 5.93 Mn |
| Mar 31, 2023 | 941,000.00 |
| Dec 31, 2022 | 1.15 Mn |
| Sep 30, 2022 | 1.35 Mn |
| Jun 30, 2022 | 1.62 Mn |
| Mar 31, 2022 | 1.87 Mn |
| Dec 31, 2021 | 2.06 Mn |
| Sep 30, 2021 | 2.26 Mn |
Wheaton Precious Metals Operating Leases 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=operating-leases&ticker=WPM&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-leases", "ticker": "WPM", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-leases&ticker=WPM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();