Trimas (TRS) Operating Expenses (2010 - 2026)
Trimas (TRS) recorded Operating Expenses of $24.5 million in Q2 2026, down 19.8% from $30.54 million a year earlier and down 18.3% from the prior quarter.
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Analysis
Trimas (TRS) Operating Expenses (2010 - 2026) Analysis & Trends
On a TTM basis, Trimas' Operating Expenses came in at $100.69 million as of Jun 30, 2026, up 6.3% year-over-year; for FY2025, it came in at $129.31 million, up 17.9% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of -0.8% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $109.65 million in FY2024 (+7.0%), $102.46 million in FY2023 (-21.9%), $131.19 million in FY2022 (+7.6%) and $121.97 million in FY2021 (-9.3%).
- Quarterly Operating Expenses has ranged from -$5.73 million in Q4 2024 to $41.14 million in Q3 2025 over the past five years.
- On a year-over-year basis, Operating Expenses rose in two of the last six quarters, with an average decline of 5.9%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 20.6% in Q3 2024, against a decline of 23.2% in Q1 2025 at the low end.
- Per Business Quant, the preceding three quarters came in at $29.99 million (Q1 2026), $5.06 million (Q4 2025) and $41.14 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 330.21 Bn | 284.21 Bn | 4.68 Bn | 10.86 Bn |
| 2 | Rtx | 252.88 Bn | 226.09 Bn | 5.13 Bn | 21.96 Bn |
| 3 | Boeing | 145.76 Bn | 52.46 Bn | 2.41 Bn | 2.35 Bn |
| 4 | Lockheed Martin | 119.56 Bn | 106.28 Bn | 2.45 Bn | - |
| 5 | Howmet Aerospace | 91.38 Bn | 86.98 Bn | 951.00 Mn | 156.00 Mn |
| 6 | General Dynamics | 90.40 Bn | 77.51 Bn | 2.18 Bn | 12.63 Bn |
| 7 | Motorola Solutions | 74.81 Bn | 71.18 Bn | 1.68 Bn | 756.00 Mn |
| 8 | Northrop Grumman | 71.85 Bn | 61.10 Bn | 2.12 Bn | 9.78 Bn |
| 9 | Honeywell International | 67.04 Bn | 19.48 Bn | 3.65 Bn | 1.87 Bn |
| 10 | Trimas | 1.41 Bn | -1.20 Bn | 35.34 Mn | 24.50 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 24.50 Mn |
| Mar 31, 2026 | 29.99 Mn |
| Dec 31, 2025 | 5.06 Mn |
| Sep 30, 2025 | 41.14 Mn |
| Jun 30, 2025 | 30.54 Mn |
| Mar 31, 2025 | 30.97 Mn |
| Dec 31, 2024 | -5.73 Mn |
| Sep 30, 2024 | 38.95 Mn |
| Jun 30, 2024 | 36.10 Mn |
| Mar 31, 2024 | 40.33 Mn |
| Dec 31, 2023 | -1.95 Mn |
| Sep 30, 2023 | 32.29 Mn |
| Jun 30, 2023 | 34.47 Mn |
| Mar 31, 2023 | 37.70 Mn |
| Dec 31, 2022 | 36.71 Mn |
| Sep 30, 2022 | 32.11 Mn |
| Jun 30, 2022 | 30.81 Mn |
| Mar 31, 2022 | 31.78 Mn |
| Dec 31, 2021 | 31.80 Mn |
| Sep 30, 2021 | 27.62 Mn |
API Access
Trimas 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=TRS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "TRS", "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=TRS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();