Ssr Mining (SSRM) Operating Expenses (2021 - 2026)
Ssr Mining's Operating Expenses came in at $36.61 million for Q2 2026, down 23.1% from $47.59 million a year earlier and down 37.6% from the prior quarter.
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Analysis
Ssr Mining (SSRM) Operating Expenses (2021 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Ssr Mining reported Operating Expenses of $205.85 million, up 25.3% year-over-year; for FY2025, it came in at $204.95 million, up 35.0% from FY2024.
- Operating Expenses carries a five-year compound annual growth rate of 20.3% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $151.79 million in FY2024 (+29.0%), $117.64 million in FY2023 (-0.7%), $118.47 million in FY2022 (+7.5%) and $110.22 million in FY2021 (+35.4%).
- The Q2 2026 figure represents the lowest quarterly Operating Expenses since Q3 2024.
- Year-over-year, Operating Expenses increased in six of the last eight quarters, with growth averaging 32.2%.
- The fastest year-over-year change in Operating Expenses over five years came in Q3 2025 (growth of 110.1%), and the weakest in Q2 2026 (a decline of 23.1%).
- Business Quant data shows SSRM's Operating Expenses at $58.68 million (Q1 2026), $45.05 million (Q4 2025) and $65.5 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Rio Tinto | 179.45 Bn | 145.58 Bn | - | - |
| 2 | Southern Copper | 169.08 Bn | 147.94 Bn | 2.90 Bn | 1.67 Bn |
| 3 | Newmont | 122.31 Bn | 90.49 Bn | 4.03 Bn | 3.02 Bn |
| 4 | Ternium | 109.20 Bn | 74.25 Bn | 941.02 Mn | -427.80 Mn |
| 5 | Freeport-Mcmoran | 103.31 Bn | 99.46 Bn | 2.19 Bn | 5.03 Bn |
| 6 | Agnico Eagle Mines | 92.04 Bn | 92.04 Bn | 2.43 Bn | 57.95 Mn |
| 7 | Barrick Mining | 68.84 Bn | 53.58 Bn | 2.90 Bn | 165.00 Mn |
| 8 | Nucor | 55.48 Bn | 46.02 Bn | 2.03 Bn | 405.00 Mn |
| 9 | ArcelorMittal | 53.16 Bn | 34.19 Bn | - | -780.00 Mn |
| 10 | Ssr Mining | 6.98 Bn | 3.47 Bn | 270.13 Mn | 36.61 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 36.61 Mn |
| Mar 31, 2026 | 58.68 Mn |
| Dec 31, 2025 | 45.05 Mn |
| Sep 30, 2025 | 65.50 Mn |
| Jun 30, 2025 | 47.59 Mn |
| Mar 31, 2025 | 45.06 Mn |
| Dec 31, 2024 | 40.41 Mn |
| Sep 30, 2024 | 31.18 Mn |
| Jun 30, 2024 | 38.01 Mn |
| Mar 31, 2024 | 29.79 Mn |
| Dec 31, 2023 | 25.89 Mn |
| Sep 30, 2023 | 32.43 Mn |
| Jun 30, 2023 | 30.27 Mn |
| Mar 31, 2023 | 29.07 Mn |
| Dec 31, 2022 | 30.63 Mn |
| Sep 30, 2022 | 31.03 Mn |
| Jun 30, 2022 | 30.71 Mn |
| Mar 31, 2022 | 27.31 Mn |
| Dec 31, 2021 | 31.73 Mn |
| Sep 30, 2021 | 23.03 Mn |
API Access
Ssr Mining Operating Expenses 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-expenses&ticker=SSRM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SSRM", "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-expenses&ticker=SSRM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();