Helmerich & Payne (HP) Operating Expenses (2009 - 2026)
Helmerich & Payne (HP) posted Operating Expenses of $846.65 million for fiscal Q3 2026 (quarter ended Jun 30, 2026), down 27.6% from $1.17 billion a year earlier and down 12.7% from the prior quarter.
Helmerich & Payne (HP) Operating Expenses (2009 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Helmerich & Payne was $3.91 billion, up 17.8% year-over-year; for FY2025 (ended Sep 30, 2025), it was $3.74 billion, up 62.8% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of 9.3% (FY2020 to FY2025).
- In prior fiscal years, Helmerich & Payne's Operating Expenses was $2.3 billion in FY2024 (-0.2%), $2.3 billion in FY2023 (+14.4%), $2.01 billion in FY2022 (+22.3%) and $1.65 billion in FY2021 (-31.2%).
- The fiscal Q3 2026 figure stands as the lowest quarterly Operating Expenses since fiscal Q1 2025.
- On a year-over-year basis, Operating Expenses increased in six of the last eight quarters, with growth averaging 38.5%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was fiscal Q3 2025, with growth of 100.1%; the weakest was fiscal Q3 2026, with a decline of 27.6%.
- According to Business Quant data, Operating Expenses for the three prior fiscal quarters was $969.28 million (Q2 2026), $1.08 billion (Q1 2026) and $1.01 billion (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Slb | 76.39 Bn | 73.50 Bn | 1.40 Bn | 324.00 Mn |
| 2 | Baker Hughes | 56.70 Bn | 19.98 Bn | 1.58 Bn | 723.00 Mn |
| 3 | TechnipFMC | 27.74 Bn | 23.88 Bn | 684.70 Mn | 2.28 Bn |
| 4 | Halliburton | 27.03 Bn | 18.79 Bn | 804.00 Mn | 4.94 Bn |
| 5 | Nov | 6.97 Bn | 1.76 Bn | 521.00 Mn | 1.04 Bn |
| 6 | Noble | 6.81 Bn | 4.74 Bn | 239.27 Mn | 689.21 Mn |
| 7 | Weatherford International | 5.95 Bn | 1.88 Bn | 333.00 Mn | 998.00 Mn |
| 8 | Transocean | 5.90 Bn | 3.61 Bn | 358.00 Mn | 812.00 Mn |
| 9 | Valaris | 5.52 Bn | 3.13 Bn | 123.70 Mn | 498.70 Mn |
| 10 | Helmerich & Payne | 3.75 Bn | 2.92 Bn | 349.94 Mn | 846.65 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 846.65 Mn |
| Mar 31, 2026 | 969.28 Mn |
| Dec 31, 2025 | 1.08 Bn |
| Sep 30, 2025 | 1.01 Bn |
| Jun 30, 2025 | 1.17 Bn |
| Mar 31, 2025 | 973.88 Mn |
| Dec 31, 2024 | 586.41 Mn |
| Sep 30, 2024 | 586.21 Mn |
| Jun 30, 2024 | 584.27 Mn |
| Mar 31, 2024 | 576.78 Mn |
| Dec 31, 2023 | 553.68 Mn |
| Sep 30, 2023 | 559.47 Mn |
| Jun 30, 2023 | 575.21 Mn |
| Mar 31, 2023 | 594.02 Mn |
| Dec 31, 2022 | 575.41 Mn |
| Sep 30, 2022 | 554.53 Mn |
| Jun 30, 2022 | 516.51 Mn |
| Mar 31, 2022 | 490.21 Mn |
| Dec 31, 2021 | 452.39 Mn |
| Sep 30, 2021 | 440.84 Mn |
Helmerich & Payne 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=HP&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "HP", "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=HP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();