Stellantis (STLA) Price to Earnings (2014 - 2025)
Stellantis' Price to Earnings came in at 81.07 for Q1 2025.
Powered by 
Analysis
Stellantis (STLA) Price to Earnings (2014 - 2025) Analysis & Trends
For FY2024, Stellantis' Price to Earnings was 6.35, up 81.1% from FY2023.
- Going back by year, Price to Earnings was 3.50 in FY2023 (+39.5%), 2.51 in FY2022 (-28.2%), 3.50 in FY2021 (-69.5%) and 11.48 in FY2020 (+78.7%).
- The Q1 2025 figure represents the highest quarterly Price to Earnings in data going back to Q4 2014.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Tesla | 1,160.73 Bn | 982.96 Bn | 5.49 Bn |
| 2 | General Motors | 75.19 Bn | -29.42 Bn | 9.28 Bn |
| 3 | Ferrari | 74.17 Bn | 66.47 Bn | 1.14 Bn |
| 4 | Ford Motor | 49.64 Bn | -84.78 Bn | 7.38 Bn |
| 5 | Honda Motor | 47.63 Bn | -102.18 Bn | 8.46 Bn |
| 6 | Toyota Motor | 28.28 Bn | -349.28 Bn | 19.83 Bn |
| 7 | Rivian Automotive | 19.71 Bn | -2.02 Bn | 176.00 Mn |
| 8 | Magna International | 17.43 Bn | 11.40 Bn | 1.63 Bn |
| 9 | Stellantis | 12.80 Bn | -148.64 Bn | 3.94 Bn |
| 10 | Li Auto | 12.62 Bn | -36.34 Bn | 417.98 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Mar 31, 2025 | 81.07 |
| Mar 31, 2020 | 10.56 |
| Dec 31, 2019 | 6.33 |
| Sep 30, 2019 | 2.79 |
| Jun 30, 2019 | 2.67 |
| Mar 31, 2019 | 6.21 |
| Dec 31, 2018 | 5.27 |
| Sep 30, 2018 | 7.23 |
| Jun 30, 2018 | 7.01 |
| Mar 31, 2018 | 7.00 |
| Dec 31, 2017 | 6.96 |
| Sep 30, 2017 | 7.85 |
| Jun 30, 2017 | 5.23 |
| Mar 31, 2017 | 7.65 |
| Dec 31, 2016 | 6.88 |
| Sep 30, 2016 | 5.30 |
| Jun 30, 2016 | 11.56 |
| Mar 31, 2016 | 15.10 |
| Dec 31, 2015 | 37.57 |
| Sep 30, 2015 | 17.22 |
API Access
Stellantis Price to Earnings 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=price-to-earnings&ticker=STLA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "price-to-earnings", "ticker": "STLA", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=price-to-earnings&ticker=STLA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();