Gerdau (GGB) Accumulated Expenses (2009 - 2026)
Gerdau (GGB) recorded Accumulated Expenses of $166.16 million in the quarter ended Jun 30, 2026, up 19.9% from $138.54 million a year earlier and up 46.5% from the prior quarter.
Gerdau (GGB) Accumulated Expenses (2009 - 2026) Analysis & Trends
As of Dec 31, 2025, Gerdau reported Accumulated Expenses of $164.02 million, down 4.3% from the prior year.
- Annual Accumulated Expenses has a five-year compound annual growth rate of 7.1% (years ended Dec 2020 to Dec 2025).
- Across earlier years, Accumulated Expenses came in at $171.43 million in the year ended Dec 31, 2024 (+1.1%), $169.51 million in the year ended Dec 31, 2023 (-17.3%), $204.98 million in the year ended Dec 31, 2022 (-4.7%) and $214.98 million in the year ended Dec 31, 2021 (+85.1%).
- Quarterly Accumulated Expenses has ranged from $96.62 million in the quarter ended Mar 31, 2023 to $214.98 million in the quarter ended Dec 31, 2021 over the past five years.
- On a year-over-year basis, Accumulated Expenses has increased for three consecutive quarters, with growth averaging 0.7% over the last eight quarters.
- Peak year-over-year performance for Accumulated Expenses in the last five years was growth of 96.2% in the quarter ended Dec 31, 2021, against a decline of 18.9% in the quarter ended Jun 30, 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $113.38 million (quarter ended Mar 31, 2026), $169.81 million (quarter ended Dec 31, 2025) and $168.72 million (quarter ended Sep 30, 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Rio Tinto | 181.90 Bn | 148.03 Bn | - |
| 2 | Southern Copper | 169.19 Bn | 148.06 Bn | 2.90 Bn |
| 3 | Newmont | 121.55 Bn | 89.73 Bn | 4.03 Bn |
| 4 | Ternium | 108.92 Bn | 73.97 Bn | 941.02 Mn |
| 5 | Freeport-Mcmoran | 100.46 Bn | 96.62 Bn | 2.19 Bn |
| 6 | Agnico Eagle Mines | 91.62 Bn | 91.62 Bn | 2.43 Bn |
| 7 | Barrick Mining | 68.12 Bn | 52.86 Bn | 2.90 Bn |
| 8 | Nucor | 53.04 Bn | 43.58 Bn | 2.03 Bn |
| 9 | ArcelorMittal | 50.74 Bn | 31.77 Bn | - |
| 10 | Gerdau | 9.44 Bn | 4.34 Bn | 558.98 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 166.16 Mn |
| Mar 31, 2026 | 113.38 Mn |
| Dec 31, 2025 | 169.81 Mn |
| Sep 30, 2025 | 168.72 Mn |
| Jun 30, 2025 | 138.54 Mn |
| Mar 31, 2025 | 99.97 Mn |
| Dec 31, 2024 | 158.07 Mn |
| Sep 30, 2024 | 176.10 Mn |
| Jun 30, 2024 | 161.72 Mn |
| Mar 31, 2024 | 121.93 Mn |
| Dec 31, 2023 | 170.86 Mn |
| Sep 30, 2023 | 161.71 Mn |
| Jun 30, 2023 | 134.88 Mn |
| Mar 31, 2023 | 96.62 Mn |
| Dec 31, 2022 | 200.79 Mn |
| Sep 30, 2022 | 182.91 Mn |
| Jun 30, 2022 | 166.33 Mn |
| Mar 31, 2022 | 110.97 Mn |
| Dec 31, 2021 | 214.98 Mn |
| Sep 30, 2021 | 186.18 Mn |
Gerdau Accumulated 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=accumulated-expenses&ticker=GGB&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-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=accumulated-expenses&ticker=GGB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();