Genuine Parts (GPC) EBITDA (2009 - 2026)
Genuine Parts' EBITDA came in at $465.97 million for Q3 2026, up 0.9% from $461.77 million a year earlier but down 1.1% from the prior quarter.
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Analysis
Genuine Parts (GPC) EBITDA (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Sep 30, 2026, Genuine Parts reported EBITDA of $1.49 billion, down 10.7% year-over-year; for FY2025, it was $1.5 billion, down 8.5% from FY2024.
- EBITDA carries a five-year compound annual growth rate of 16.9% (FY2020 to FY2025).
- Going back by year, EBITDA was $1.64 billion in FY2024 (-21.9%), $2.1 billion in FY2023 (+6.9%), $1.96 billion in FY2022 (+34.9%) and $1.45 billion in FY2021 (+111.4%).
- The five-year range for quarterly EBITDA is $133.67 million (Q4 2025) to $593.89 million (Q2 2022).
- Year-over-year, EBITDA increased in four of the last eight quarters, with an average decline of 11.4%.
- The fastest year-over-year change in EBITDA over five years came in Q2 2022 (growth of 77.4%), and the weakest in Q4 2025 (a decline of 55.7%).
- Business Quant data shows GPC's EBITDA at $471.05 million (Q2 2026), $417.3 million (Q1 2026) and $133.67 million (Q4 2025) in the three quarters before Q3 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,979.57 Bn | 2,476.24 Bn | 107.37 Bn | 49.03 Bn |
| 2 | Home Depot | 350.34 Bn | 343.58 Bn | 16.12 Bn | 7.95 Bn |
| 3 | Tjx Companies | 150.76 Bn | 128.31 Bn | 5.07 Bn | 2.33 Bn |
| 4 | Lowes Companies | 130.11 Bn | 123.07 Bn | 8.58 Bn | 4.20 Bn |
| 5 | Carvana | 80.38 Bn | 71.27 Bn | 1.52 Bn | 784.00 Mn |
| 6 | Ross Stores | 76.38 Bn | 59.31 Bn | 2.12 Bn | 1.24 Bn |
| 7 | Target | 73.52 Bn | 68.11 Bn | 8.94 Bn | 3.34 Bn |
| 8 | O Reilly Automotive | 71.92 Bn | 71.02 Bn | 2.68 Bn | 1.24 Bn |
| 9 | Autozone | 52.04 Bn | 50.89 Bn | 3.52 Bn | 1.54 Bn |
| 10 | Genuine Parts | 17.20 Bn | 14.91 Bn | 2.48 Bn | 139.52 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 139.52 Mn |
| Jun 30, 2026 | 136.74 Mn |
| Mar 31, 2026 | 133.05 Mn |
| Dec 31, 2025 | 172.10 Mn |
| Sep 30, 2025 | 129.50 Mn |
| Jun 30, 2025 | 125.04 Mn |
| Mar 31, 2025 | 117.46 Mn |
| Dec 31, 2024 | 112.13 Mn |
| Sep 30, 2024 | 108.06 Mn |
| Jun 30, 2024 | 101.23 Mn |
| Mar 31, 2024 | 92.63 Mn |
| Dec 31, 2023 | 507.27 Mn |
| Sep 30, 2023 | 549.03 Mn |
| Jun 30, 2023 | 544.77 Mn |
| Mar 31, 2023 | 496.52 Mn |
| Dec 31, 2022 | 435.56 Mn |
| Sep 30, 2022 | 515.10 Mn |
| Jun 30, 2022 | 593.89 Mn |
| Mar 31, 2022 | 417.47 Mn |
| Dec 31, 2021 | 410.68 Mn |
API Access
Genuine Parts 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=GPC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "GPC", "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=GPC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();