Magnolia Oil & Gas (MGY) Operating Expenses (2017 - 2026)
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Analysis
Magnolia Oil & Gas (MGY) Operating Expenses (2017 - 2026) Analysis & Trends
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | ExxonMobil Holdings | 696.20 Bn | 661.07 Bn | 47.44 Bn | 91.93 Bn |
| 2 | Shell | 563.81 Bn | 425.16 Bn | - | -177.00 Mn |
| 3 | Chevron | 432.14 Bn | 404.83 Bn | 31.26 Bn | 54.17 Bn |
| 4 | TotalEnergies SE | 200.31 Bn | 75.66 Bn | 31.61 Bn | 5.11 Bn |
| 5 | Eni Spa | 181.16 Bn | 124.34 Bn | - | - |
| 6 | Conocophillips | 168.32 Bn | 137.35 Bn | 12.63 Bn | 2.44 Bn |
| 7 | Equinor Asa | 107.41 Bn | 20.34 Bn | 4.49 Bn | 30.42 Bn |
| 8 | Canadian Natural Resources | 103.54 Bn | 97.44 Bn | 9.35 Bn | 590.04 Mn |
| 9 | Phillips 66 | 103.32 Bn | 88.28 Bn | 10.69 Bn | 44.40 Bn |
| 10 | Magnolia Oil & Gas | 6.54 Bn | 5.83 Bn | 494.29 Mn | 359.29 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 359.29 Mn |
| Jun 30, 2026 | 239.31 Mn |
| Mar 31, 2026 | 230.75 Mn |
| Dec 31, 2025 | 223.55 Mn |
| Sep 30, 2025 | 223.47 Mn |
| Jun 30, 2025 | 211.17 Mn |
| Mar 31, 2025 | 214.48 Mn |
| Dec 31, 2024 | 202.54 Mn |
| Sep 30, 2024 | 204.12 Mn |
| Jun 30, 2024 | 202.37 Mn |
| Mar 31, 2024 | 194.86 Mn |
| Dec 31, 2023 | 184.54 Mn |
| Sep 30, 2023 | 167.55 Mn |
| Jun 30, 2023 | 158.96 Mn |
| Mar 31, 2023 | 181.45 Mn |
| Dec 31, 2022 | 151.14 Mn |
| Sep 30, 2022 | 171.21 Mn |
| Jun 30, 2022 | 156.39 Mn |
| Mar 31, 2022 | 141.97 Mn |
| Dec 31, 2021 | 130.14 Mn |
API Access
Magnolia Oil & Gas 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=MGY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "MGY", "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=MGY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();