Realty Income (O) Provision for Losses (2025 - 2026)
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Analysis
Realty Income (O) Provision for Losses (2025 - 2026) Analysis & Trends
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Provision for Losses (Qtr) |
|---|---|---|---|---|---|
| 1 | Welltower | 163.27 Bn | 144.76 Bn | 1.39 Bn | 2.18 Mn |
| 2 | Prologis | 123.38 Bn | 118.42 Bn | - | - |
| 3 | Simon Property | 64.69 Bn | 60.54 Bn | - | - |
| 4 | Realty Income | 51.11 Bn | 49.33 Bn | - | 7.26 Mn |
| 5 | Public Storage | 50.26 Bn | 49.25 Bn | - | - |
| 6 | Ventas | 40.91 Bn | 39.60 Bn | - | - |
| 7 | Extra Space Storage | 28.00 Bn | 28.00 Bn | 642.43 Mn | - |
| 8 | Vici Properties | 24.79 Bn | 22.91 Bn | 1.05 Bn | - |
| 9 | Vivmark Residential | 22.68 Bn | 22.46 Bn | - | - |
| 10 | Essex Property Trust | 17.33 Bn | 17.10 Bn | - | -256,000.00 |
API Access
Realty Income Provision for Losses 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=provision-for-losses&ticker=O&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "provision-for-losses", "ticker": "O", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=provision-for-losses&ticker=O&period=max&api_key=YOUR_API_KEY");
const data = await res.json();