Federal Signal (FSS) Operating Expenses (2010 - 2026)
Federal Signal (FSS) posted Operating Expenses of $78.3 million for Q2 2026, up 17.0% from $66.9 million a year earlier and up 8.8% from the prior quarter.
Federal Signal (FSS) Operating Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Federal Signal was $279.1 million, up 13.6% year-over-year; for FY2025, it came in at $255.9 million, up 9.4% from FY2024.
- Annual Operating Expenses has increased for four consecutive years, with a five-year compound annual growth rate of 11.2% (FY2020 to FY2025).
- In prior years, Federal Signal's Operating Expenses was $234 million in FY2024 (+11.4%), $210.1 million in FY2023 (+22.4%), $171.7 million in FY2022 (+15.1%) and $149.2 million in FY2021 (-0.9%).
- The Q2 2026 figure stands as the highest quarterly Operating Expenses in data going back to Q2 2010.
- On a year-over-year basis, Operating Expenses has increased in each of the last 19 quarters, with growth averaging 12.6% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q3 2023, with growth of 27.1%; the weakest was Q3 2021, with a decline of 13.0%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $72 million (Q1 2026), $67.4 million (Q4 2025) and $61.4 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Tenaris | 63.59 Bn | 34.88 Bn | 984.66 Mn | 484.11 Mn |
| 2 | Rockwell Automation | 47.72 Bn | 45.91 Bn | 1.14 Bn | 663.00 Mn |
| 3 | Hubbell | 24.28 Bn | 22.20 Bn | 613.00 Mn | 264.40 Mn |
| 4 | Graco | 10.60 Bn | 8.61 Bn | 296.22 Mn | 76.61 Mn |
| 5 | Allison Transmission Holdings | 8.85 Bn | 5.75 Bn | 515.00 Mn | 224.00 Mn |
| 6 | Advanced Energy Industries | 8.85 Bn | 5.20 Bn | 236.10 Mn | 141.00 Mn |
| 7 | Flowserve | 8.84 Bn | 5.79 Bn | 384.73 Mn | 286.40 Mn |
| 8 | Pentair | 8.82 Bn | 8.43 Bn | 395.00 Mn | 228.50 Mn |
| 9 | MSA Safety | 7.05 Bn | 6.33 Bn | 249.29 Mn | 135.44 Mn |
| 10 | Federal Signal | 6.98 Bn | 6.72 Bn | 203.80 Mn | 78.30 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 78.30 Mn |
| Mar 31, 2026 | 72.00 Mn |
| Dec 31, 2025 | 67.40 Mn |
| Sep 30, 2025 | 61.40 Mn |
| Jun 30, 2025 | 66.90 Mn |
| Mar 31, 2025 | 60.20 Mn |
| Dec 31, 2024 | 58.40 Mn |
| Sep 30, 2024 | 60.10 Mn |
| Jun 30, 2024 | 58.30 Mn |
| Mar 31, 2024 | 57.20 Mn |
| Dec 31, 2023 | 54.10 Mn |
| Sep 30, 2023 | 50.60 Mn |
| Jun 30, 2023 | 53.40 Mn |
| Mar 31, 2023 | 52.00 Mn |
| Dec 31, 2022 | 46.20 Mn |
| Sep 30, 2022 | 39.80 Mn |
| Jun 30, 2022 | 42.10 Mn |
| Mar 31, 2022 | 43.60 Mn |
| Dec 31, 2021 | 37.60 Mn |
| Sep 30, 2021 | 33.40 Mn |
Federal Signal 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=FSS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "FSS", "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=FSS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();