Park Aerospace (PKE) Operating Expenses (2010 - 2026)
Park Aerospace (PKE) posted Operating Expenses of $2.36 million for fiscal Q1 2027 (quarter ended May 31, 2026), up 2.7% from $2.3 million a year earlier and up 0.8% from the prior quarter.
Park Aerospace (PKE) Operating Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through May 31, 2026, Operating Expenses at Park Aerospace was $9.23 million, up 8.3% year-over-year; for FY2026 (ended Mar 1, 2026), it was $9.17 million, up 11.2% from FY2025.
- Annual Operating Expenses has increased for four consecutive fiscal years, with a five-year compound annual growth rate of 3.6% (FY2021 to FY2026).
- In prior fiscal years, Park Aerospace's Operating Expenses was $8.25 million in FY2025 (+1.1%), $8.15 million in FY2024 (+25.1%), $6.52 million in FY2023 (+0.2%) and $6.51 million in FY2022 (-15.3%).
- The fiscal Q1 2027 figure stands as the highest quarterly Operating Expenses since fiscal Q1 2024.
- On a year-over-year basis, Operating Expenses has increased in each of the last eight quarters, with growth averaging 10.7% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was fiscal Q1 2024, with growth of 60.1%; the weakest was fiscal Q4 2022, with a decline of 46.6%.
- According to Business Quant data, Operating Expenses for the three prior fiscal quarters was $2.34 million (Q4 2026), $2.26 million (Q3 2026) and $2.27 million (Q2 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Linde | 231.45 Bn | 213.03 Bn | 4.43 Bn | 928.00 Mn |
| 2 | Corning | 116.59 Bn | 109.15 Bn | 1.63 Bn | 907.00 Mn |
| 3 | Sherwin Williams | 82.19 Bn | 81.23 Bn | 3.34 Bn | 2.10 Bn |
| 4 | Air Products & Chemicals | 67.40 Bn | 62.58 Bn | 1.04 Bn | 3.15 Bn |
| 5 | LyondellBasell Industries | 40.93 Bn | 30.44 Bn | 2.04 Bn | 7.63 Bn |
| 6 | Nutrien | 33.12 Bn | 29.95 Bn | 3.25 Bn | 235.00 Mn |
| 7 | Qnity Electronics | 25.20 Bn | 22.33 Bn | 666.00 Mn | 298.00 Mn |
| 8 | Ppg Industries | 24.54 Bn | 17.20 Bn | 1.81 Bn | 1.15 Bn |
| 9 | Ati | 24.54 Bn | 22.56 Bn | 309.80 Mn | 99.60 Mn |
| 10 | Park Aerospace | 554.19 Mn | 197.11 Mn | 7.14 Mn | 2.40 Mn |
Historic Data
| Date | Value |
|---|---|
| Aug 30, 2026 | 2.40 Mn |
| May 31, 2026 | 2.36 Mn |
| Mar 1, 2026 | 2.34 Mn |
| Nov 30, 2025 | 2.26 Mn |
| Aug 31, 2025 | 2.27 Mn |
| Jun 1, 2025 | 2.30 Mn |
| Mar 2, 2025 | 2.11 Mn |
| Dec 1, 2024 | 1.98 Mn |
| Sep 1, 2024 | 2.14 Mn |
| Jun 2, 2024 | 2.02 Mn |
| Mar 3, 2024 | 1.88 Mn |
| Nov 26, 2023 | 1.80 Mn |
| Aug 27, 2023 | 1.85 Mn |
| May 28, 2023 | 2.62 Mn |
| Feb 26, 2023 | 1.63 Mn |
| Nov 27, 2022 | 1.52 Mn |
| Aug 28, 2022 | 1.73 Mn |
| May 29, 2022 | 1.63 Mn |
| Feb 27, 2022 | 1.58 Mn |
| Nov 28, 2021 | 1.61 Mn |
Park Aerospace 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=PKE&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "PKE", "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=PKE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();