Gerdau (GGB) Operating Expenses (2009 - 2026)
Gerdau (GGB) reported Operating Expenses of $64.78 million for Q3 2026, up 11.6% from $58.07 million a year earlier but down 0.1% from the prior quarter.
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Analysis
Gerdau (GGB) Operating Expenses (2009 - 2026) Analysis & Trends
Over the twelve months ended Sep 30, 2026, Gerdau's Operating Expenses came in at $398.26 million, up 5.5% year-over-year; for FY2025, it was $379.95 million, down 6.0% from FY2024.
- Operating Expenses has a five-year compound annual growth rate of 4.8% (FY2020 to FY2025).
- By year, Operating Expenses came in at $404.32 million in FY2024 (-8.6%), $442.41 million in FY2023 (+4.2%), $424.51 million in FY2022 (+8.5%) and $391.08 million in FY2021 (+30.2%).
- Five-year quarterly Operating Expenses spans a low of $58.07 million in Q3 2025 and a high of $222.36 million in Q4 2023.
- Year over year, Operating Expenses has now increased in each of the last four quarters, with an average decline of 0.9% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was Q4 2022 (growth of 185.2%); the low point was Q1 2023 (a decline of 25.9%).
- Per Business Quant data, the three quarters before Q3 2026 came in at $64.82 million (Q2 2026), $63.9 million (Q1 2026) and $204.77 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Rio Tinto | 170.99 Bn | 133.79 Bn | - | - |
| 2 | Southern Copper | 142.57 Bn | 117.30 Bn | 3.10 Bn | 1.88 Bn |
| 3 | Rio Tinto | 132.80 Bn | 93.63 Bn | - | - |
| 4 | Newmont | 113.01 Bn | 78.15 Bn | 4.22 Bn | 3.20 Bn |
| 5 | Freeport-Mcmoran | 88.56 Bn | 72.60 Bn | 2.19 Bn | 5.03 Bn |
| 6 | Agnico Eagle Mines | 84.41 Bn | 71.36 Bn | 2.15 Bn | 146.67 Mn |
| 7 | Barrick Mining | 63.76 Bn | 38.96 Bn | 2.90 Bn | 165.00 Mn |
| 8 | Nucor | 62.69 Bn | 52.07 Bn | 2.03 Bn | 405.00 Mn |
| 9 | ArcelorMittal | 46.21 Bn | 25.24 Bn | - | 780.00 Mn |
| 10 | Gerdau | 9.29 Bn | 4.61 Bn | 651.76 Mn | 64.78 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 64.78 Mn |
| Jun 30, 2026 | 64.82 Mn |
| Mar 31, 2026 | 63.90 Mn |
| Dec 31, 2025 | 204.77 Mn |
| Sep 30, 2025 | 58.07 Mn |
| Jun 30, 2025 | 62.09 Mn |
| Mar 31, 2025 | 59.55 Mn |
| Dec 31, 2024 | 197.83 Mn |
| Sep 30, 2024 | 63.93 Mn |
| Jun 30, 2024 | 66.25 Mn |
| Mar 31, 2024 | 64.29 Mn |
| Dec 31, 2023 | 222.36 Mn |
| Sep 30, 2023 | 72.71 Mn |
| Jun 30, 2023 | 78.39 Mn |
| Mar 31, 2023 | 70.06 Mn |
| Dec 31, 2022 | 219.01 Mn |
| Sep 30, 2022 | 70.86 Mn |
| Jun 30, 2022 | 68.94 Mn |
| Mar 31, 2022 | 94.58 Mn |
| Dec 31, 2021 | 76.80 Mn |
API Access
Gerdau 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=GGB&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "GGB", "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=GGB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();