Park Ohio Holdings (PKOH) Operating Expenses (2010 - 2026)
Park Ohio Holdings' Operating Expenses was $54.4 million in Q2 2026, up 13.1% from $48.1 million a year earlier and up 2.6% from the prior quarter.
Park Ohio Holdings (PKOH) Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Park Ohio Holdings' Operating Expenses was $206.1 million through Jun 30, 2026, up 6.5% year-over-year; for FY2025, it came in at $196 million, up 1.9% from FY2024.
- Operating Expenses has now increased for five consecutive years, with a five-year compound annual growth rate of 6.0% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $192.3 million in FY2024 (+2.2%), $188.1 million in FY2023 (+4.8%), $179.5 million in FY2022 (+1.8%) and $176.3 million in FY2021 (+20.1%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses in data going back to Q2 2010.
- Compared with a year earlier, Operating Expenses has increased for four straight quarters, with growth averaging 5.6% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q4 2022 (growth of 88.5%); the worst was Q4 2023 (a decline of 11.5%).
- Per Business Quant data, PKOH's Operating Expenses in the three quarters before Q2 2026 was $53 million (Q1 2026), $49.4 million (Q4 2025) and $49.3 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Caterpillar | 372.79 Bn | 344.49 Bn | 7.76 Bn | 16.25 Bn |
| 2 | Amphenol | 207.98 Bn | 202.68 Bn | 3.55 Bn | 963.40 Mn |
| 3 | Deere | 181.02 Bn | 189.78 Bn | 4.66 Bn | 10.73 Bn |
| 4 | Eaton | 166.86 Bn | 164.09 Bn | 2.86 Bn | 1.46 Bn |
| 5 | Parker-Hannifin | 120.45 Bn | 118.58 Bn | 2.25 Bn | 874.00 Mn |
| 6 | Vertiv Holdings | 92.94 Bn | 83.56 Bn | 1.23 Bn | 490.50 Mn |
| 7 | Emerson Electric | 86.56 Bn | 79.32 Bn | 2.66 Bn | 1.34 Bn |
| 8 | 3M | 84.72 Bn | 66.18 Bn | 2.68 Bn | 5.52 Bn |
| 9 | Illinois Tool Works | 73.32 Bn | 69.88 Bn | 1.90 Bn | - |
| 10 | Park Ohio Holdings | 669.44 Mn | 480.24 Mn | 78.90 Mn | 54.40 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 54.40 Mn |
| Mar 31, 2026 | 53.00 Mn |
| Dec 31, 2025 | 49.40 Mn |
| Sep 30, 2025 | 49.30 Mn |
| Jun 30, 2025 | 48.10 Mn |
| Mar 31, 2025 | 49.20 Mn |
| Dec 31, 2024 | 47.60 Mn |
| Sep 30, 2024 | 48.70 Mn |
| Jun 30, 2024 | 48.60 Mn |
| Mar 31, 2024 | 47.40 Mn |
| Dec 31, 2023 | 46.40 Mn |
| Sep 30, 2023 | 43.00 Mn |
| Jun 30, 2023 | 50.90 Mn |
| Mar 31, 2023 | 47.80 Mn |
| Dec 31, 2022 | 52.40 Mn |
| Sep 30, 2022 | 40.80 Mn |
| Jun 30, 2022 | 42.80 Mn |
| Mar 31, 2022 | 43.50 Mn |
| Dec 31, 2021 | 27.80 Mn |
| Sep 30, 2021 | 45.10 Mn |
Park Ohio Holdings 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=PKOH&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "PKOH", "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=PKOH&period=max&api_key=YOUR_API_KEY");
const data = await res.json();