Park Ohio Holdings (PKOH) Accumulated Expenses (2010 - 2026)
Park Ohio Holdings (PKOH) posted Accumulated Expenses of $139.9 million for Q2 2026, up 17.0% from $119.6 million a year earlier but down 3.6% from the prior quarter.
Park Ohio Holdings (PKOH) Accumulated Expenses (2010 - 2026) Analysis & Trends
At the end of FY2025, Park Ohio Holdings' Accumulated Expenses came in at $147.6 million, up 0.3% from FY2024.
- Annual Accumulated Expenses has increased for four consecutive years, with a five-year compound annual growth rate of 24.0% (FY2020 to FY2025).
- In prior years, Park Ohio Holdings' Accumulated Expenses was $147.2 million in FY2024 (+36.5%), $107.8 million in FY2023 (+14.2%), $94.4 million in FY2022 (+120.6%) and $42.8 million in FY2021 (-15.1%).
- Quarterly Accumulated Expenses has run from a low of $42.8 million in Q4 2021 to a high of $191.8 million in Q3 2023 over five years.
- On a year-over-year basis, Accumulated Expenses has increased in each of the last three quarters, with an average decline of 1.0% over the last eight quarters.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was Q4 2022, with growth of 120.6%; the weakest was Q3 2024, with a decline of 28.4%.
- According to Business Quant data, Accumulated Expenses for the three prior quarters was $145.1 million (Q1 2026), $147.6 million (Q4 2025) and $129.7 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Caterpillar | 372.79 Bn | 344.49 Bn | 7.76 Bn |
| 2 | Amphenol | 207.98 Bn | 202.68 Bn | 3.55 Bn |
| 3 | Deere | 181.02 Bn | 189.78 Bn | 4.66 Bn |
| 4 | Eaton | 166.86 Bn | 164.09 Bn | 2.86 Bn |
| 5 | Parker-Hannifin | 120.45 Bn | 118.58 Bn | 2.25 Bn |
| 6 | Vertiv Holdings | 92.94 Bn | 83.56 Bn | 1.23 Bn |
| 7 | Emerson Electric | 86.56 Bn | 79.32 Bn | 2.66 Bn |
| 8 | 3M | 84.72 Bn | 66.18 Bn | 2.68 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 |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 139.90 Mn |
| Mar 31, 2026 | 145.10 Mn |
| Dec 31, 2025 | 147.60 Mn |
| Sep 30, 2025 | 129.70 Mn |
| Jun 30, 2025 | 119.60 Mn |
| Mar 31, 2025 | 142.70 Mn |
| Dec 31, 2024 | 147.20 Mn |
| Sep 30, 2024 | 137.40 Mn |
| Jun 30, 2024 | 137.50 Mn |
| Mar 31, 2024 | 170.30 Mn |
| Dec 31, 2023 | 107.80 Mn |
| Sep 30, 2023 | 191.80 Mn |
| Jun 30, 2023 | 159.80 Mn |
| Mar 31, 2023 | 163.80 Mn |
| Dec 31, 2022 | 94.40 Mn |
| Sep 30, 2022 | 119.30 Mn |
| Jun 30, 2022 | 111.00 Mn |
| Mar 31, 2022 | 139.50 Mn |
| Dec 31, 2021 | 42.80 Mn |
| Sep 30, 2021 | 122.10 Mn |
Park Ohio Holdings Accumulated 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=accumulated-expenses&ticker=PKOH&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-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=accumulated-expenses&ticker=PKOH&period=max&api_key=YOUR_API_KEY");
const data = await res.json();