Steel Dynamics (STLD) Operating Expenses (2009 - 2026)
Steel Dynamics (STLD) posted Operating Expenses of $193.45 million for Q2 2026, down 2.3% from $198.01 million a year earlier but up 10.4% from the prior quarter.
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Analysis
Steel Dynamics (STLD) Operating Expenses (2009 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Steel Dynamics was $754.16 million, up 4.1% year-over-year; for FY2025, it came in at $765.31 million, up 15.2% from FY2024.
- Annual Operating Expenses has increased for three consecutive years, with a four-year compound annual growth rate of 4.4% (FY2021 to FY2025).
- In prior years, Steel Dynamics' Operating Expenses was $664.12 million in FY2024 (+12.8%), $588.62 million in FY2023 (+7.9%), $545.62 million in FY2022 (-15.3%) and $643.98 million in FY2021.
- Quarterly Operating Expenses has run from a low of $141.21 million in Q2 2023 to a high of $200.84 million in Q3 2025 over five years.
- On a year-over-year basis, Operating Expenses increased in six of the last eight quarters, with growth averaging 10.4%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q2 2025, with growth of 23.7%; the weakest was Q1 2026, with a decline of 3.6%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $175.22 million (Q1 2026), $184.65 million (Q4 2025) and $200.84 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Rio Tinto | 182.38 Bn | 151.41 Bn | - | - |
| 2 | Southern Copper | 169.97 Bn | 148.75 Bn | 2.90 Bn | 1.67 Bn |
| 3 | Rio Tinto | 143.92 Bn | 104.42 Bn | - | - |
| 4 | Newmont | 125.84 Bn | 93.84 Bn | 4.03 Bn | 3.02 Bn |
| 5 | Freeport-Mcmoran | 99.89 Bn | 83.93 Bn | 2.19 Bn | 5.03 Bn |
| 6 | Agnico Eagle Mines | 94.91 Bn | 84.54 Bn | 2.43 Bn | 119.48 Mn |
| 7 | Barrick Mining | 69.68 Bn | 44.88 Bn | 2.90 Bn | 165.00 Mn |
| 8 | Nucor | 59.90 Bn | 49.28 Bn | 2.03 Bn | 405.00 Mn |
| 9 | ArcelorMittal | 48.48 Bn | 27.50 Bn | - | -780.00 Mn |
| 10 | Steel Dynamics | 35.42 Bn | 32.50 Bn | 958.97 Mn | 193.45 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 193.45 Mn |
| Mar 31, 2026 | 175.22 Mn |
| Dec 31, 2025 | 184.65 Mn |
| Sep 30, 2025 | 200.84 Mn |
| Jun 30, 2025 | 198.01 Mn |
| Mar 31, 2025 | 181.81 Mn |
| Dec 31, 2024 | 176.90 Mn |
| Sep 30, 2024 | 167.69 Mn |
| Jun 30, 2024 | 160.02 Mn |
| Mar 31, 2024 | 159.51 Mn |
| Dec 31, 2023 | 157.21 Mn |
| Sep 30, 2023 | 145.90 Mn |
| Jun 30, 2023 | 141.21 Mn |
| Mar 31, 2023 | 144.31 Mn |
| Sep 30, 2019 | 131.79 Mn |
| Jun 30, 2019 | 136.13 Mn |
| Mar 31, 2019 | 141.73 Mn |
| Dec 31, 2018 | 155.68 Mn |
| Sep 30, 2018 | 154.51 Mn |
| Jun 30, 2018 | 150.20 Mn |
API Access
Steel Dynamics 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=STLD&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "STLD", "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=STLD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();