Goodyear Tire & Rubber (GT) Land & Improvements (2019 - 2023)
Goodyear Tire & Rubber's Land & Improvements came in at $462 million for Q4 2023, up 2.7% from $450 million a year earlier.
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Analysis
Goodyear Tire & Rubber (GT) Land & Improvements (2019 - 2023) Analysis & Trends
Going back to Q4 2019, Goodyear Tire & Rubber's Land & Improvements data covers 5 quarters.
- Land & Improvements carries a four-year compound annual growth rate of 2.0% (FY2019 to FY2023).
- Going back by year, Land & Improvements was $450 million in FY2022 (-18.6%), $553 million in FY2021 (+26.5%), $437 million in FY2020 (+2.6%) and $426 million in FY2019.
- The Q4 2023 figure represents the highest quarterly Land & Improvements since Q4 2021.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Land & Improvements (Qtr) |
|---|---|---|---|---|---|
| 1 | Tesla | 1,230.49 Bn | 1,061.40 Bn | 5.49 Bn | - |
| 2 | Ferrari | 154.33 Bn | 146.64 Bn | 1.14 Bn | - |
| 3 | General Motors | 75.30 Bn | -27.60 Bn | 9.28 Bn | - |
| 4 | Ford Motor | 48.13 Bn | -86.25 Bn | -12.63 Bn | - |
| 5 | Toyota Motor | 28.58 Bn | -348.98 Bn | 19.83 Bn | 8.60 Bn |
| 6 | Rivian Automotive | 20.00 Bn | -1.70 Bn | 176.00 Mn | - |
| 7 | Magna International | 17.18 Bn | 11.48 Bn | 1.63 Bn | - |
| 8 | Li Auto | 12.66 Bn | -36.22 Bn | 417.98 Mn | - |
| 9 | Stellantis | 12.34 Bn | -148.56 Bn | 3.94 Bn | - |
| 10 | Goodyear Tire & Rubber | 1.16 Bn | -1.88 Bn | 723.00 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2023 | 462.00 Mn |
| Dec 31, 2022 | 450.00 Mn |
| Dec 31, 2021 | 553.00 Mn |
| Dec 31, 2020 | 437.00 Mn |
| Dec 31, 2019 | 426.00 Mn |
API Access
Goodyear Tire & Rubber Land & Improvements 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=land-and-improvements&ticker=GT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "land-and-improvements", "ticker": "GT", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=land-and-improvements&ticker=GT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();