Minerals Technologies (MTX) Other Accumulated Expenses (2009 - 2026)
Minerals Technologies (MTX) posted Other Accumulated Expenses of $624.1 million for Q3 2026, up 66.6% from $374.7 million a year earlier and up 1.7% from the prior quarter.
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Analysis
Minerals Technologies (MTX) Other Accumulated Expenses (2009 - 2026) Analysis & Trends
At the end of FY2025, Minerals Technologies' Other Accumulated Expenses came in at $360.8 million, up 241.3% from FY2024.
- Annual Other Accumulated Expenses shows a five-year compound annual growth rate of 36.0% (FY2020 to FY2025).
- In prior years, Minerals Technologies' Other Accumulated Expenses was $105.7 million in FY2024 (+14.9%), $92 million in FY2023 (-16.2%), $109.8 million in FY2022 (+29.2%) and $85 million in FY2021 (+9.7%).
- The Q3 2026 figure stands as the highest quarterly Other Accumulated Expenses in data going back to Q4 2009.
- On a year-over-year basis, Other Accumulated Expenses increased in seven of the last eight quarters, with growth averaging 93.1%.
- The strongest year-over-year quarter for Other Accumulated Expenses in the past five years was Q4 2025, with growth of 241.3%; the weakest was Q4 2023, with a decline of 16.2%.
- According to Business Quant data, Other Accumulated Expenses for the three prior quarters was $613.9 million (Q2 2026), $331.5 million (Q1 2026) and $360.8 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Nucor | 175.24 Bn | 165.01 Bn | 2.33 Bn |
| 2 | Rio Tinto | 166.15 Bn | 128.95 Bn | - |
| 3 | Southern Copper | 143.83 Bn | 118.64 Bn | 3.10 Bn |
| 4 | Rio Tinto | 137.31 Bn | 104.37 Bn | - |
| 5 | Newmont | 124.66 Bn | 89.98 Bn | 4.22 Bn |
| 6 | Ternium | 102.52 Bn | 75.29 Bn | 1.04 Bn |
| 7 | Agnico Eagle Mines | 95.19 Bn | 82.13 Bn | 2.15 Bn |
| 8 | Freeport-Mcmoran | 86.53 Bn | 83.18 Bn | 2.55 Bn |
| 9 | Barrick Mining | 66.50 Bn | 50.91 Bn | 2.71 Bn |
| 10 | Minerals Technologies | 1.92 Bn | 572.58 Mn | 129.20 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Oct 4, 2026 | 624.10 Mn |
| Jul 5, 2026 | 613.90 Mn |
| Apr 5, 2026 | 331.50 Mn |
| Dec 31, 2025 | 360.80 Mn |
| Sep 28, 2025 | 374.70 Mn |
| Jun 29, 2025 | 380.50 Mn |
| Mar 30, 2025 | 383.70 Mn |
| Dec 31, 2024 | 105.70 Mn |
| Sep 29, 2024 | 186.00 Mn |
| Jun 30, 2024 | 175.50 Mn |
| Mar 31, 2024 | 150.00 Mn |
| Dec 31, 2023 | 92.00 Mn |
| Oct 1, 2023 | 165.10 Mn |
| Jul 2, 2023 | 146.30 Mn |
| Apr 2, 2023 | 154.20 Mn |
| Dec 31, 2022 | 109.80 Mn |
| Oct 2, 2022 | 164.20 Mn |
| Jul 3, 2022 | 135.80 Mn |
| Apr 3, 2022 | 125.90 Mn |
| Dec 31, 2021 | 85.00 Mn |
API Access
Minerals Technologies Other 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=other-accumulated-expenses&ticker=MTX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-accumulated-expenses", "ticker": "MTX", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=other-accumulated-expenses&ticker=MTX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();