Genuine Parts (GPC) Acquisitions (2009 - 2026)
Genuine Parts (GPC) posted Acquisitions of $31.84 million for Q3 2026, down 54.5% from $70.01 million a year earlier but up 33.7% from the prior quarter.
Genuine Parts (GPC) Acquisitions (2009 - 2026) Analysis & Trends
For the trailing twelve months through Sep 30, 2026, Acquisitions at Genuine Parts was $205.75 million, down 33.2% year-over-year; for FY2025, it came in at $318.29 million, down 70.5% from FY2024.
- Annual Acquisitions shows a five-year compound annual growth rate of 35.7% (FY2020 to FY2025).
- In prior years, Genuine Parts' Acquisitions was $1.08 billion in FY2024 (+252.0%), $306.88 million in FY2023 (-81.8%), $1.69 billion in FY2022 (+494.5%) and $284.32 million in FY2021 (+311.0%).
- Quarterly Acquisitions has run from a low of $13.8 million in Q1 2026 to a high of $1.35 billion in Q1 2022 over five years.
- On a year-over-year basis, Acquisitions has declined in each of the last three quarters, with an average decline of 42.6% over the last eight quarters.
- The strongest year-over-year quarter for Acquisitions in the past five years was Q2 2024, with growth of 572.0%; the weakest was Q1 2023, with a decline of 97.1%.
- According to Business Quant data, Acquisitions for the three prior quarters was $23.82 million (Q2 2026), $13.8 million (Q1 2026) and $136.3 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Acquisitions (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,931.82 Bn | 2,428.49 Bn | 107.37 Bn | 23.99 Bn |
| 2 | Home Depot | 348.68 Bn | 341.92 Bn | 16.12 Bn | 1.05 Bn |
| 3 | Tjx Companies | 150.97 Bn | 128.51 Bn | 5.07 Bn | - |
| 4 | Lowes Companies | 128.03 Bn | 120.99 Bn | 8.58 Bn | - |
| 5 | Ross Stores | 74.86 Bn | 57.79 Bn | 2.12 Bn | - |
| 6 | O Reilly Automotive | 73.48 Bn | 72.56 Bn | 2.52 Bn | - |
| 7 | Target | 72.25 Bn | 66.84 Bn | 8.94 Bn | - |
| 8 | Carvana | 53.50 Bn | 43.09 Bn | 1.52 Bn | - |
| 9 | Autozone | 53.15 Bn | 52.00 Bn | 3.52 Bn | - |
| 10 | Genuine Parts | 17.21 Bn | 14.91 Bn | 2.48 Bn | 31.84 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 31.84 Mn |
| Jun 30, 2026 | 23.82 Mn |
| Mar 31, 2026 | 13.80 Mn |
| Dec 31, 2025 | 136.30 Mn |
| Sep 30, 2025 | 70.01 Mn |
| Jun 30, 2025 | 37.85 Mn |
| Mar 31, 2025 | 74.13 Mn |
| Dec 31, 2024 | 126.03 Mn |
| Sep 30, 2024 | 373.07 Mn |
| Jun 30, 2024 | 446.46 Mn |
| Mar 31, 2024 | 134.68 Mn |
| Dec 31, 2023 | 88.70 Mn |
| Sep 30, 2023 | 112.15 Mn |
| Jun 30, 2023 | 66.44 Mn |
| Mar 31, 2023 | 39.59 Mn |
| Dec 31, 2022 | 136.02 Mn |
| Sep 30, 2022 | 22.87 Mn |
| Jun 30, 2022 | 182.52 Mn |
| Mar 31, 2022 | 1.35 Bn |
| Dec 31, 2021 | 141.75 Mn |
Genuine Parts Acquisitions 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=acquisitions&ticker=GPC&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "acquisitions", "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=acquisitions&ticker=GPC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();