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 | 1,148.52 Bn | 983.08 Bn | 4.75 Bn | - |
| 2 | Toyota Motor | 242.17 Bn | -164.57 Bn | 20.95 Bn | 8.55 Bn |
| 3 | Ferrari | 145.86 Bn | 138.30 Bn | 1.18 Bn | - |
| 4 | Honda Motor | 143.38 Bn | 10.76 Bn | 8.46 Bn | - |
| 5 | General Motors | 67.56 Bn | -37.30 Bn | 7.33 Bn | - |
| 6 | Ford Motor | 47.24 Bn | -95.23 Bn | 6.08 Bn | - |
| 7 | Rivian Automotive | 20.35 Bn | -2.94 Bn | 179.00 Mn | - |
| 8 | Magna International | 17.85 Bn | 15.41 Bn | 1.61 Bn | - |
| 9 | Stellantis | 12.63 Bn | -153.36 Bn | 5.55 Bn | - |
| 10 | Goodyear Tire & Rubber | 1.43 Bn | -1.60 Bn | 681.00 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();