Steel Dynamics (STLD) Change in Accured Expenses (2009 - 2026)
Steel Dynamics' Change in Accured Expenses came in at $126.05 million for Q2 2026, up 222.9% from $39.03 million a year earlier.
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Analysis
Steel Dynamics (STLD) Change in Accured Expenses (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Steel Dynamics reported Change in Accured Expenses of $78.23 million; for FY2025, it came in at -$43.19 million.
- Going back by year, Change in Accured Expenses was -$102.04 million in FY2024, -$164.78 million in FY2023, $63.68 million in FY2022 (-84.6%) and $414.21 million in FY2021.
- The five-year range for quarterly Change in Accured Expenses is -$417.92 million (Q1 2023) to $169.82 million (Q3 2021).
- Year-over-year, Change in Accured Expenses increased in two of the last five quarters, with growth averaging 17.0%.
- The fastest year-over-year change in Change in Accured Expenses over five years came in Q4 2021 (growth of 400.4%), and the weakest in Q4 2024 (a decline of 98.0%).
- Business Quant data shows STLD's Change in Accured Expenses at -$163.03 million (Q1 2026), -$12.09 million (Q4 2025) and $127.3 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Rio Tinto | 193.68 Bn | 159.81 Bn | - | - |
| 2 | Southern Copper | 171.36 Bn | 150.22 Bn | 2.90 Bn | 107.70 Mn |
| 3 | Newmont | 121.76 Bn | 89.94 Bn | 4.03 Bn | -166.00 Mn |
| 4 | Ternium | 113.51 Bn | 78.56 Bn | 941.02 Mn | - |
| 5 | Freeport-Mcmoran | 103.45 Bn | 99.60 Bn | 2.19 Bn | 309.00 Mn |
| 6 | Agnico Eagle Mines | 91.92 Bn | 91.92 Bn | 2.43 Bn | -106.54 Mn |
| 7 | Barrick Mining | 67.42 Bn | 52.16 Bn | 2.90 Bn | - |
| 8 | Nucor | 54.54 Bn | 45.08 Bn | 2.03 Bn | 298.00 Mn |
| 9 | ArcelorMittal | 49.09 Bn | 30.12 Bn | - | - |
| 10 | Steel Dynamics | 33.32 Bn | 30.19 Bn | 958.97 Mn | 126.05 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 126.05 Mn |
| Mar 31, 2026 | -163.03 Mn |
| Dec 31, 2025 | -12.09 Mn |
| Sep 30, 2025 | 127.30 Mn |
| Jun 30, 2025 | 39.03 Mn |
| Mar 31, 2025 | -197.43 Mn |
| Dec 31, 2024 | 600,000.00 |
| Sep 30, 2024 | 100.84 Mn |
| Jun 30, 2024 | 76.56 Mn |
| Mar 31, 2024 | -280.04 Mn |
| Dec 31, 2023 | 30.76 Mn |
| Sep 30, 2023 | 121.76 Mn |
| Jun 30, 2023 | 100.61 Mn |
| Mar 31, 2023 | -417.92 Mn |
| Dec 31, 2022 | 32.55 Mn |
| Sep 30, 2022 | 149.77 Mn |
| Jun 30, 2022 | 140.02 Mn |
| Mar 31, 2022 | -258.66 Mn |
| Dec 31, 2021 | 135.97 Mn |
| Sep 30, 2021 | 169.82 Mn |
API Access
Steel Dynamics Change in Accured 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=change-in-accured-expenses&ticker=STLD&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-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=change-in-accured-expenses&ticker=STLD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();