Group 1 Automotive (GPI) Operating Expenses (2010 - 2026)
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Analysis
Group 1 Automotive (GPI) Operating Expenses (2010 - 2026) Analysis & Trends
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,887.17 Bn | 2,383.84 Bn | 107.37 Bn | 173.87 Bn |
| 2 | Home Depot | 352.83 Bn | 346.07 Bn | 16.12 Bn | 9.28 Bn |
| 3 | Tjx Companies | 152.69 Bn | 130.24 Bn | 5.07 Bn | 3.09 Bn |
| 4 | Lowes Companies | 129.94 Bn | 122.90 Bn | 8.58 Bn | 4.46 Bn |
| 5 | Target | 75.44 Bn | 70.03 Bn | 8.94 Bn | 5.73 Bn |
| 6 | Ross Stores | 75.40 Bn | 58.32 Bn | 2.12 Bn | 1.02 Bn |
| 7 | O Reilly Automotive | 74.28 Bn | 73.37 Bn | 2.52 Bn | 1.53 Bn |
| 8 | Carvana | 54.79 Bn | 44.38 Bn | 1.52 Bn | 805.00 Mn |
| 9 | Autozone | 53.72 Bn | 52.57 Bn | 3.52 Bn | 2.20 Bn |
| 10 | Group 1 Automotive | 3.17 Bn | 2.05 Bn | 854.80 Mn | 618.30 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 618.30 Mn |
| Jun 30, 2026 | 625.60 Mn |
| Mar 31, 2026 | 601.60 Mn |
| Dec 31, 2025 | 635.40 Mn |
| Sep 30, 2025 | 656.50 Mn |
| Jun 30, 2025 | 653.70 Mn |
| Mar 31, 2025 | 628.40 Mn |
| Dec 31, 2024 | 631.00 Mn |
| Sep 30, 2024 | 591.60 Mn |
| Jun 30, 2024 | 497.20 Mn |
| Mar 31, 2024 | 476.10 Mn |
| Dec 31, 2023 | 487.40 Mn |
| Sep 30, 2023 | 496.70 Mn |
| Jun 30, 2023 | 479.90 Mn |
| Mar 31, 2023 | 462.80 Mn |
| Dec 31, 2022 | 453.70 Mn |
| Sep 30, 2022 | 450.90 Mn |
| Jun 30, 2022 | 460.20 Mn |
| Mar 31, 2022 | 418.50 Mn |
| Dec 31, 2021 | 421.00 Mn |
API Access
Group 1 Automotive 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=GPI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "GPI", "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=GPI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();