Penske Automotive (PAG) EBITDA (2009 - 2026)
Penske Automotive's EBITDA came in at $383 million for Q2 2026, down 6.2% from $408.4 million a year earlier but up 14.7% from the prior quarter.
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Analysis
Penske Automotive (PAG) EBITDA (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Penske Automotive reported EBITDA of $1.42 billion, down 9.2% year-over-year; for FY2025, it came in at $1.45 billion, down 5.1% from FY2024.
- EBITDA has declined in each of the last three years, though with a five-year compound annual growth rate of 12.1% (FY2020 to FY2025).
- Going back by year, EBITDA was $1.53 billion in FY2024 (-1.4%), $1.55 billion in FY2023 (-3.8%), $1.62 billion in FY2022 (+9.3%) and $1.48 billion in FY2021 (+80.2%).
- The five-year range for quarterly EBITDA is $333.8 million (Q1 2026) to $433.9 million (Q1 2022).
- Year-over-year, EBITDA has declined for four consecutive quarters, with an average decline of 1.2% over the last eight quarters.
- The fastest year-over-year change in EBITDA over five years came in Q1 2022 (growth of 74.3%), and the weakest in Q4 2025 (a decline of 15.2%).
- Business Quant data shows PAG's EBITDA at $333.8 million (Q1 2026), $365.7 million (Q4 2025) and $341.6 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,829.78 Bn | 2,346.48 Bn | 104.83 Bn | 47.45 Bn |
| 2 | Home Depot | 290.18 Bn | 283.42 Bn | 16.12 Bn | 7.95 Bn |
| 3 | Tjx Companies | 152.80 Bn | 130.34 Bn | 5.07 Bn | 2.33 Bn |
| 4 | Lowes Companies | 104.32 Bn | 97.29 Bn | 8.58 Bn | 4.20 Bn |
| 5 | Ross Stores | 71.10 Bn | 54.02 Bn | 2.12 Bn | 1.24 Bn |
| 6 | O Reilly Automotive | 70.56 Bn | 69.64 Bn | 2.52 Bn | 1.13 Bn |
| 7 | Carvana | 70.07 Bn | 61.67 Bn | 1.38 Bn | 753.00 Mn |
| 8 | Target | 69.82 Bn | 64.41 Bn | 8.94 Bn | 3.34 Bn |
| 9 | Autozone | 48.00 Bn | 46.90 Bn | 2.52 Bn | 1.09 Bn |
| 10 | Penske Automotive | 12.88 Bn | 12.60 Bn | 1.36 Bn | 383.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 383.00 Mn |
| Mar 31, 2026 | 333.80 Mn |
| Dec 31, 2025 | 365.70 Mn |
| Sep 30, 2025 | 341.60 Mn |
| Jun 30, 2025 | 408.40 Mn |
| Mar 31, 2025 | 370.00 Mn |
| Dec 31, 2024 | 431.40 Mn |
| Sep 30, 2024 | 358.00 Mn |
| Jun 30, 2024 | 376.60 Mn |
| Mar 31, 2024 | 365.40 Mn |
| Dec 31, 2023 | 363.80 Mn |
| Sep 30, 2023 | 366.90 Mn |
| Jun 30, 2023 | 414.90 Mn |
| Mar 31, 2023 | 407.40 Mn |
| Dec 31, 2022 | 367.70 Mn |
| Sep 30, 2022 | 394.20 Mn |
| Jun 30, 2022 | 419.30 Mn |
| Mar 31, 2022 | 433.90 Mn |
| Dec 31, 2021 | 388.10 Mn |
| Sep 30, 2021 | 408.00 Mn |
API Access
Penske Automotive EBITDA 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=ebitda&ticker=PAG&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "PAG", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=ebitda&ticker=PAG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();