American Realty Investors (ARL) Operating Expenses (2010 - 2026)
American Realty Investors (ARL) posted Operating Expenses of $15.42 million for Q2 2026, up 17.0% from $13.17 million a year earlier and up 6.1% from the prior quarter.
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Analysis
American Realty Investors (ARL) Operating Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at American Realty Investors was $60.4 million, up 12.9% year-over-year; for FY2025, it was $56.44 million, up 4.6% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of -0.9% (FY2020 to FY2025).
- In prior years, American Realty Investors' Operating Expenses was $53.96 million in FY2024 (-12.6%), $61.74 million in FY2023 (+31.9%), $46.81 million in FY2022 (-25.3%) and $62.66 million in FY2021 (+6.0%).
- Quarterly Operating Expenses has run from a low of $11.16 million in Q2 2022 to a high of $16.24 million in Q4 2023 over five years.
- On a year-over-year basis, Operating Expenses has increased in each of the last five quarters, with growth averaging 3.4% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q2 2023, with growth of 44.2%; the weakest was Q2 2022, with a decline of 43.8%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $14.53 million (Q1 2026), $16.04 million (Q4 2025) and $14.41 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Texas Pacific Land | 22.47 Bn | 21.30 Bn | - | 54.24 Mn |
| 2 | Eason Technology | 6.75 Bn | 6.75 Bn | - | - |
| 3 | LandBridge | 6.25 Bn | 6.60 Bn | 65.71 Mn | 15.90 Mn |
| 4 | Millrose Properties | 4.01 Bn | 4.01 Bn | - | 29.22 Mn |
| 5 | St Joe | 3.75 Bn | 3.25 Bn | 73.42 Mn | 104.06 Mn |
| 6 | Vesta Real Estate Corporation, S.A.B. de C.V | 2.85 Bn | 2.85 Bn | - | -8.70 Mn |
| 7 | Opendoor Technologies | 2.30 Bn | -1.52 Bn | 86.00 Mn | 230.00 Mn |
| 8 | Forestar | 1.31 Bn | -34.86 Mn | 84.10 Mn | 38.30 Mn |
| 9 | Five Point Holdings | 693.74 Mn | 722.51 Mn | -23.72 Mn | 21.49 Mn |
| 10 | American Realty Investors | 268.61 Mn | 463.62 Mn | - | 15.42 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 15.42 Mn |
| Mar 31, 2026 | 14.53 Mn |
| Dec 31, 2025 | 16.04 Mn |
| Sep 30, 2025 | 14.41 Mn |
| Jun 30, 2025 | 13.17 Mn |
| Mar 31, 2025 | 12.82 Mn |
| Dec 31, 2024 | 13.82 Mn |
| Sep 30, 2024 | 13.67 Mn |
| Jun 30, 2024 | 13.05 Mn |
| Mar 31, 2024 | 13.42 Mn |
| Dec 31, 2023 | 16.24 Mn |
| Sep 30, 2023 | 14.63 Mn |
| Jun 30, 2023 | 16.10 Mn |
| Mar 31, 2023 | 14.77 Mn |
| Dec 31, 2022 | 11.86 Mn |
| Sep 30, 2022 | 11.51 Mn |
| Jun 30, 2022 | 11.16 Mn |
| Mar 31, 2022 | 12.28 Mn |
| Dec 31, 2021 | 12.29 Mn |
| Sep 30, 2021 | 15.66 Mn |
API Access
American Realty Investors 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=ARL&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ARL", "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=ARL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();