Getty Realty (GTY) Buildings (2010 - 2019)
Getty Realty (GTY) posted Buildings of $275,000 for Q1 2019.
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Analysis
Getty Realty (GTY) Buildings (2010 - 2019) Analysis & Trends
At the end of FY2016, Getty Realty's Buildings came in at $528,000, down 47.0% from FY2015.
- Annual Buildings shows a five-year compound annual growth rate of -71.3% (FY2011 to FY2016).
- In prior years, Getty Realty's Buildings was $997,000 in FY2015 (-99.6%), $246.11 million in FY2014 (+25.2%), $196.61 million in FY2013 (-5.6%) and $208.33 million in FY2012 (-23.0%).
- The Q1 2019 figure stands as the highest quarterly Buildings since Q1 2017.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Welltower | 166.01 Bn | 148.52 Bn | 1.39 Bn |
| 2 | Prologis | 121.16 Bn | 125.55 Bn | - |
| 3 | Simon Property | 65.49 Bn | 66.75 Bn | - |
| 4 | Realty Income | 51.38 Bn | 53.76 Bn | - |
| 5 | Public Storage | 49.67 Bn | 48.75 Bn | - |
| 6 | Ventas | 43.61 Bn | 42.81 Bn | - |
| 7 | Extra Space Storage | 27.79 Bn | 27.79 Bn | 642.43 Mn |
| 8 | Vici Properties | 25.29 Bn | 23.41 Bn | 1.05 Bn |
| 9 | Vivmark Residential | 22.78 Bn | 22.97 Bn | - |
| 10 | Getty Realty | 1.75 Bn | 1.75 Bn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Mar 31, 2019 | 275,000.00 |
| Sep 30, 2018 | 209,000.00 |
| Mar 31, 2017 | 678,000.00 |
| Dec 31, 2016 | 528,000.00 |
| Sep 30, 2016 | 439,000.00 |
| Jun 30, 2016 | 531,000.00 |
| Mar 31, 2016 | 594,000.00 |
| Dec 31, 2015 | 997,000.00 |
| Dec 31, 2014 | 246.11 Mn |
| Sep 30, 2014 | 196.78 Mn |
| Jun 30, 2014 | 197.57 Mn |
| Mar 31, 2014 | 196.72 Mn |
| Dec 31, 2013 | 196.61 Mn |
| Sep 30, 2013 | 202.47 Mn |
| Jun 30, 2013 | 202.47 Mn |
| Mar 31, 2013 | 191.50 Mn |
| Dec 31, 2012 | 208.33 Mn |
| Sep 30, 2012 | 224.00 Mn |
| Jun 30, 2012 | 251.94 Mn |
| Mar 31, 2012 | 270.90 Mn |
API Access
Getty Realty Buildings 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=buildings&ticker=GTY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "buildings", "ticker": "GTY", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=buildings&ticker=GTY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();