Albemarle (ALB) Accumulated Expenses (2009 - 2026)
Albemarle (ALB) posted Accumulated Expenses of $507.56 million for Q2 2026, up 22.3% from $414.88 million a year earlier and up 12.1% from the prior quarter.
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Analysis
Albemarle (ALB) Accumulated Expenses (2009 - 2026) Analysis & Trends
At the end of FY2025, Albemarle's Accumulated Expenses came in at $521.83 million, up 11.5% from FY2024.
- Annual Accumulated Expenses shows a five-year compound annual growth rate of 3.4% (FY2020 to FY2025).
- In prior years, Albemarle's Accumulated Expenses was $468 million in FY2024 (-14.1%), $544.84 million in FY2023 (+7.7%), $505.89 million in FY2022 (-33.7%) and $763.29 million in FY2021 (+73.2%).
- Quarterly Accumulated Expenses has run from a low of $330.94 million in Q2 2022 to a high of $956.51 million in Q3 2021 over five years.
- On a year-over-year basis, Accumulated Expenses has increased in each of the last three quarters, with an average decline of 3.0% over the last eight quarters.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was Q2 2023, with growth of 103.3%; the weakest was Q3 2022, with a decline of 59.7%.
- According to Business Quant data, Accumulated Expenses for the three prior quarters was $452.93 million (Q1 2026), $521.83 million (Q4 2025) and $500.94 million (Q3 2025).
Peer Set
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 | Albemarle | 12.48 Bn | 6.47 Bn | 590.30 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 507.56 Mn |
| Mar 31, 2026 | 452.93 Mn |
| Dec 31, 2025 | 521.83 Mn |
| Sep 30, 2025 | 500.94 Mn |
| Jun 30, 2025 | 414.88 Mn |
| Mar 31, 2025 | 379.87 Mn |
| Dec 31, 2024 | 468.00 Mn |
| Sep 30, 2024 | 513.12 Mn |
| Jun 30, 2024 | 508.33 Mn |
| Mar 31, 2024 | 454.60 Mn |
| Dec 31, 2023 | 544.84 Mn |
| Sep 30, 2023 | 689.11 Mn |
| Jun 30, 2023 | 672.81 Mn |
| Mar 31, 2023 | 403.34 Mn |
| Dec 31, 2022 | 505.89 Mn |
| Sep 30, 2022 | 385.33 Mn |
| Jun 30, 2022 | 330.94 Mn |
| Mar 31, 2022 | 667.61 Mn |
| Dec 31, 2021 | 763.29 Mn |
| Sep 30, 2021 | 956.51 Mn |
API Access
Albemarle 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=ALB&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "ALB", "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=ALB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();