Minerals Technologies (MTX) Operating Expenses (2009 - 2026)
Minerals Technologies (MTX) recorded Operating Expenses of $59.2 million in Q2 2026, down 7.1% from $63.7 million a year earlier and down 6.9% from the prior quarter.
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Analysis
Minerals Technologies (MTX) Operating Expenses (2009 - 2026) Analysis & Trends
On a TTM basis, Minerals Technologies' Operating Expenses came in at $243.1 million as of Jul 5, 2026, up 1.2% year-over-year; for FY2025, it was $245.9 million, up 5.9% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 3.8% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $232.2 million in FY2024 (-0.8%), $234.1 million in FY2023 (+7.6%), $217.6 million in FY2022 (+3.8%) and $209.7 million in FY2021 (+2.8%).
- Quarterly Operating Expenses has ranged from $51.6 million in Q3 2021 to $64 million in Q2 2023 over the past five years.
- On a year-over-year basis, Operating Expenses rose in six of the last eight quarters, with growth averaging 2.8%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 13.5% in Q2 2023, against a decline of 7.7% in Q2 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at $63.6 million (Q1 2026), $61.7 million (Q4 2025) and $58.6 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Rio Tinto | 182.38 Bn | 151.41 Bn | - | - |
| 2 | Southern Copper | 167.30 Bn | 146.09 Bn | 2.90 Bn | 1.67 Bn |
| 3 | Rio Tinto | 143.04 Bn | 103.54 Bn | - | - |
| 4 | Newmont | 124.35 Bn | 92.35 Bn | 4.03 Bn | 3.02 Bn |
| 5 | Freeport-Mcmoran | 99.09 Bn | 83.13 Bn | 2.19 Bn | 5.03 Bn |
| 6 | Agnico Eagle Mines | 93.47 Bn | 83.11 Bn | 2.43 Bn | 119.48 Mn |
| 7 | Barrick Mining | 69.01 Bn | 44.20 Bn | 2.90 Bn | 165.00 Mn |
| 8 | Nucor | 59.68 Bn | 49.06 Bn | 2.03 Bn | 405.00 Mn |
| 9 | ArcelorMittal | 48.25 Bn | 27.28 Bn | - | -780.00 Mn |
| 10 | Minerals Technologies | 1.95 Bn | 617.84 Mn | 133.80 Mn | 59.20 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 5, 2026 | 59.20 Mn |
| Apr 5, 2026 | 63.60 Mn |
| Dec 31, 2025 | 61.70 Mn |
| Sep 28, 2025 | 58.60 Mn |
| Jun 29, 2025 | 63.70 Mn |
| Mar 30, 2025 | 61.90 Mn |
| Dec 31, 2024 | 58.50 Mn |
| Sep 29, 2024 | 56.00 Mn |
| Jun 30, 2024 | 59.10 Mn |
| Mar 31, 2024 | 58.60 Mn |
| Dec 31, 2023 | 56.10 Mn |
| Oct 1, 2023 | 56.40 Mn |
| Jul 2, 2023 | 64.00 Mn |
| Apr 2, 2023 | 57.70 Mn |
| Dec 31, 2022 | 54.10 Mn |
| Oct 2, 2022 | 51.60 Mn |
| Jul 3, 2022 | 56.40 Mn |
| Apr 3, 2022 | 55.50 Mn |
| Dec 31, 2021 | 53.40 Mn |
| Oct 3, 2021 | 51.60 Mn |
API Access
Minerals Technologies 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=MTX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-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=operating-expenses&ticker=MTX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();