JBG SMITH Properties (JBGS) Operating Expenses (2016 - 2026)
JBG SMITH Properties (JBGS) posted Operating Expenses of $125.52 million for Q2 2026, down 2.1% from $128.21 million a year earlier and down 7.5% from the prior quarter.
JBG SMITH Properties (JBGS) Operating Expenses (2016 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at JBG SMITH Properties was $512.89 million, down 0.9% year-over-year; for FY2025, it was $506.63 million, down 7.2% from FY2024.
- Annual Operating Expenses has declined for four consecutive years, with a five-year compound annual growth rate of -4.6% (FY2020 to FY2025).
- In prior years, JBG SMITH Properties' Operating Expenses was $545.77 million in FY2024 (-3.4%), $564.98 million in FY2023 (-4.2%), $589.65 million in FY2022 (-8.7%) and $645.5 million in FY2021 (+0.8%).
- Quarterly Operating Expenses has run from a low of $124.78 million in Q3 2025 to a high of $162.9 million in Q1 2022 over five years.
- On a year-over-year basis, Operating Expenses increased in 1 of the last eight quarters, with an average decline of 4.3%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q1 2026, with growth of 7.1%; the weakest was Q3 2022, with a decline of 14.1%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $135.7 million (Q1 2026), $126.9 million (Q4 2025) and $124.78 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Welltower | 167.90 Bn | 150.42 Bn | 1.39 Bn | 3.22 Bn |
| 2 | Prologis | 123.74 Bn | 128.13 Bn | - | 1.47 Bn |
| 3 | Simon Property | 66.68 Bn | 67.94 Bn | - | 900.79 Mn |
| 4 | Realty Income | 52.20 Bn | 54.59 Bn | - | 1.19 Bn |
| 5 | Public Storage | 50.15 Bn | 49.24 Bn | - | 766.20 Mn |
| 6 | Ventas | 44.59 Bn | 43.78 Bn | - | 1.68 Bn |
| 7 | Extra Space Storage | 28.21 Bn | 28.21 Bn | 642.43 Mn | 481.97 Mn |
| 8 | Vici Properties | 25.53 Bn | 23.65 Bn | 1.05 Bn | 315.61 Mn |
| 9 | Vivmark Residential | 23.00 Bn | 23.19 Bn | - | 566.18 Mn |
| 10 | JBG SMITH Properties | 753.40 Mn | 1.25 Bn | - | 125.52 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 125.52 Mn |
| Mar 31, 2026 | 135.70 Mn |
| Dec 31, 2025 | 126.90 Mn |
| Sep 30, 2025 | 124.78 Mn |
| Jun 30, 2025 | 128.21 Mn |
| Mar 31, 2025 | 126.74 Mn |
| Dec 31, 2024 | 132.83 Mn |
| Sep 30, 2024 | 129.76 Mn |
| Jun 30, 2024 | 138.43 Mn |
| Mar 31, 2024 | 144.74 Mn |
| Dec 31, 2023 | 140.91 Mn |
| Sep 30, 2023 | 136.79 Mn |
| Jun 30, 2023 | 140.24 Mn |
| Mar 31, 2023 | 147.04 Mn |
| Dec 31, 2022 | 147.63 Mn |
| Sep 30, 2022 | 136.77 Mn |
| Jun 30, 2022 | 142.36 Mn |
| Mar 31, 2022 | 162.90 Mn |
| Dec 31, 2021 | 162.02 Mn |
| Sep 30, 2021 | 159.26 Mn |
JBG SMITH Properties Operating Expenses 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=operating-expenses&ticker=JBGS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "JBGS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=JBGS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();