STAG Industrial (STAG) Operating Expenses (2010 - 2026)
STAG Industrial (STAG) reported Operating Expenses of $141.27 million for Q2 2026, up 9.8% from $128.61 million a year earlier and up 0.8% from the prior quarter.
STAG Industrial (STAG) Operating Expenses (2010 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, STAG Industrial's Operating Expenses came in at $549.65 million, up 7.7% year-over-year; for FY2025, it came in at $528.24 million, up 4.7% from FY2024.
- Operating Expenses has increased for 15 consecutive years, with a five-year compound annual growth rate of 8.5% (FY2020 to FY2025).
- By year, Operating Expenses came in at $504.41 million in FY2024 (+7.3%), $470.23 million in FY2023 (+3.6%), $453.85 million in FY2022 (+14.0%) and $398.19 million in FY2021 (+13.2%).
- The Q2 2026 figure ranks as the highest quarterly Operating Expenses in data going back to Q2 2010.
- Year over year, Operating Expenses has now increased in each of the last four quarters, with growth averaging 5.9% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was Q2 2022 (growth of 15.8%); the low point was Q2 2025 (a decline of 1.2%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $140.2 million (Q1 2026), $137.31 million (Q4 2025) and $130.87 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Welltower | 166.01 Bn | 148.52 Bn | 1.39 Bn | 3.22 Bn |
| 2 | Prologis | 121.16 Bn | 125.55 Bn | - | 1.47 Bn |
| 3 | Simon Property | 65.49 Bn | 66.75 Bn | - | 900.79 Mn |
| 4 | Realty Income | 51.38 Bn | 53.76 Bn | - | 1.19 Bn |
| 5 | Public Storage | 49.67 Bn | 48.75 Bn | - | 766.20 Mn |
| 6 | Ventas | 43.61 Bn | 42.81 Bn | - | 1.68 Bn |
| 7 | Extra Space Storage | 27.79 Bn | 27.79 Bn | 642.43 Mn | 481.97 Mn |
| 8 | Vici Properties | 25.29 Bn | 23.41 Bn | 1.05 Bn | 315.61 Mn |
| 9 | Vivmark Residential | 22.78 Bn | 22.97 Bn | - | 566.18 Mn |
| 10 | STAG Industrial | 6.91 Bn | 6.98 Bn | - | 141.27 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 141.27 Mn |
| Mar 31, 2026 | 140.20 Mn |
| Dec 31, 2025 | 137.31 Mn |
| Sep 30, 2025 | 130.87 Mn |
| Jun 30, 2025 | 128.61 Mn |
| Mar 31, 2025 | 131.46 Mn |
| Dec 31, 2024 | 127.20 Mn |
| Sep 30, 2024 | 123.04 Mn |
| Jun 30, 2024 | 130.15 Mn |
| Mar 31, 2024 | 124.01 Mn |
| Dec 31, 2023 | 120.10 Mn |
| Sep 30, 2023 | 116.06 Mn |
| Jun 30, 2023 | 113.59 Mn |
| Mar 31, 2023 | 120.48 Mn |
| Dec 31, 2022 | 118.19 Mn |
| Sep 30, 2022 | 112.79 Mn |
| Jun 30, 2022 | 110.92 Mn |
| Mar 31, 2022 | 111.95 Mn |
| Dec 31, 2021 | 103.89 Mn |
| Sep 30, 2021 | 99.48 Mn |
STAG Industrial 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=STAG&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "STAG", "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=STAG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();