Tutor Perini (TPC) Operating Expenses (2011 - 2026)
Tutor Perini (TPC) posted Operating Expenses of $93.54 million for Q2 2026, down 21.8% from $119.57 million a year earlier and down 2.0% from the prior quarter.
Tutor Perini (TPC) Operating Expenses (2011 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Tutor Perini was $415.91 million, up 20.1% year-over-year; for FY2025, it came in at $415.55 million, up 38.2% from FY2024.
- Annual Operating Expenses has increased for three consecutive years, with a five-year compound annual growth rate of 13.2% (FY2020 to FY2025).
- In prior years, Tutor Perini's Operating Expenses was $300.79 million in FY2024 (+17.9%), $255.22 million in FY2023 (+8.9%), $234.38 million in FY2022 (-2.2%) and $239.59 million in FY2021 (+7.0%).
- The Q2 2026 figure stands as the lowest quarterly Operating Expenses since Q1 2025.
- On a year-over-year basis, Operating Expenses increased in seven of the last eight quarters, with growth averaging 24.8%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q3 2025, with growth of 59.7%; the weakest was Q2 2026, with a decline of 21.8%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $95.45 million (Q1 2026), $97.61 million (Q4 2025) and $129.3 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Quanta Services | 90.28 Bn | 88.36 Bn | 1.55 Bn | 698.49 Mn |
| 2 | Ferrovial | 35.35 Bn | 13.60 Bn | - | - |
| 3 | Emcor | 31.22 Bn | 27.61 Bn | 1.02 Bn | 475.04 Mn |
| 4 | Jacobs Solutions | 16.38 Bn | 11.05 Bn | 810.70 Mn | 524.00 Mn |
| 5 | Mastec | 14.71 Bn | 13.49 Bn | 556.28 Mn | 292.57 Mn |
| 6 | Sterling Infrastructure | 12.68 Bn | 11.00 Bn | 289.96 Mn | 65.66 Mn |
| 7 | IES Holdings | 9.66 Bn | 8.52 Bn | 340.66 Mn | 162.17 Mn |
| 8 | Stantec | 7.88 Bn | 6.81 Bn | 1.36 Bn | 972.05 Mn |
| 9 | Aecom | 7.58 Bn | 2.70 Bn | -34.04 Mn | 46.45 Mn |
| 10 | Tutor Perini | 4.11 Bn | 4.84 Mn | 211.28 Mn | 93.54 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 93.54 Mn |
| Mar 31, 2026 | 95.45 Mn |
| Dec 31, 2025 | 97.61 Mn |
| Sep 30, 2025 | 129.30 Mn |
| Jun 30, 2025 | 119.57 Mn |
| Mar 31, 2025 | 69.08 Mn |
| Dec 31, 2024 | 76.78 Mn |
| Sep 30, 2024 | 80.98 Mn |
| Jun 30, 2024 | 76.59 Mn |
| Mar 31, 2024 | 66.45 Mn |
| Dec 31, 2023 | 71.39 Mn |
| Sep 30, 2023 | 63.48 Mn |
| Jun 30, 2023 | 62.57 Mn |
| Mar 31, 2023 | 57.78 Mn |
| Dec 31, 2022 | 60.56 Mn |
| Sep 30, 2022 | 57.23 Mn |
| Jun 30, 2022 | 56.33 Mn |
| Mar 31, 2022 | 60.25 Mn |
| Dec 31, 2021 | 58.22 Mn |
| Sep 30, 2021 | 61.88 Mn |
Tutor Perini 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=TPC&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "TPC", "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=TPC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();