Intergroup (INTG) Operating Expenses (2010 - 2026)
Intergroup's Operating Expenses was $15.51 million in fiscal Q4 2026 (quarter ended Jun 30, 2026), up 4.1% from $14.9 million a year earlier but down 3.8% from the prior quarter.
Intergroup (INTG) Operating Expenses (2010 - 2026) Analysis & Trends
For FY2026 (ended Jun 30, 2026), Operating Expenses at Intergroup came in at $62.09 million, up 9.4% from FY2025.
- Operating Expenses shows a five-year compound annual growth rate of 13.1% (FY2021 to FY2026).
- In earlier fiscal years, Operating Expenses was $56.74 million in FY2025 (+7.4%), $52.85 million in FY2024 (-0.8%), $53.27 million in FY2023 (+22.3%) and $43.55 million in FY2022 (+29.9%).
- Quarterly Operating Expenses has moved between $10.37 million (fiscal Q1 2022) and $48.16 million (fiscal Q4 2024) over five years.
- Compared with a year earlier, Operating Expenses has increased for four straight quarters, with an average decline of 5.4% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was fiscal Q4 2024 (growth of 280.1%); the worst was fiscal Q4 2025 (a decline of 69.1%).
- Per Business Quant data, INTG's Operating Expenses in the three fiscal quarters before Q4 2026 was $16.11 million (Q3 2026), $15.29 million (Q2 2026) and $15.18 million (Q1 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Texas Pacific Land | 23.47 Bn | 22.30 Bn | - | 54.24 Mn |
| 2 | LandBridge | 6.46 Bn | 6.80 Bn | 65.71 Mn | 15.90 Mn |
| 3 | Eason Technology | 6.34 Bn | 6.34 Bn | - | - |
| 4 | Millrose Properties | 3.80 Bn | 3.80 Bn | - | 29.22 Mn |
| 5 | St Joe | 3.73 Bn | 3.23 Bn | 73.42 Mn | 104.06 Mn |
| 6 | Vesta Real Estate Corporation, S.A.B. de C.V | 2.87 Bn | 2.87 Bn | - | -8.70 Mn |
| 7 | Opendoor Technologies | 2.36 Bn | -1.46 Bn | 86.00 Mn | 230.00 Mn |
| 8 | Forestar | 1.31 Bn | -33.33 Mn | 84.10 Mn | 38.30 Mn |
| 9 | Five Point Holdings | 674.47 Mn | 703.24 Mn | -23.72 Mn | 21.49 Mn |
| 10 | Intergroup | 59.97 Mn | 231,342.59 | 7.37 Mn | 15.51 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 15.51 Mn |
| Mar 31, 2026 | 16.11 Mn |
| Dec 31, 2025 | 15.29 Mn |
| Sep 30, 2025 | 15.18 Mn |
| Jun 30, 2025 | 50.88 Mn |
| Mar 31, 2025 | 14.47 Mn |
| Dec 31, 2024 | 13.59 Mn |
| Sep 30, 2024 | 13.78 Mn |
| Jun 30, 2024 | 48.16 Mn |
| Mar 31, 2024 | 14.17 Mn |
| Dec 31, 2023 | 15.67 Mn |
| Sep 30, 2023 | 13.91 Mn |
| Jun 30, 2023 | 12.67 Mn |
| Mar 31, 2023 | 13.40 Mn |
| Dec 31, 2022 | 13.68 Mn |
| Sep 30, 2022 | 13.53 Mn |
| Jun 30, 2022 | 12.14 Mn |
| Mar 31, 2022 | 10.58 Mn |
| Dec 31, 2021 | 10.47 Mn |
| Sep 30, 2021 | 10.37 Mn |
Intergroup 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=INTG&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "INTG", "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=INTG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();