St Joe (JOE) Operating Expenses (2009 - 2026)
St Joe (JOE) posted Operating Expenses of $104.06 million for Q2 2026, up 13.0% from $92.12 million a year earlier and up 28.7% from the prior quarter.
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Analysis
St Joe (JOE) Operating Expenses (2009 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at St Joe was $382.51 million, up 17.4% year-over-year; for FY2025, it was $367.02 million, up 19.5% from FY2024.
- Annual Operating Expenses has increased for seven consecutive years, with a five-year compound annual growth rate of 26.5% (FY2020 to FY2025).
- In prior years, St Joe's Operating Expenses was $307.15 million in FY2024 (+2.9%), $298.55 million in FY2023 (+56.4%), $190.85 million in FY2022 (+10.6%) and $172.54 million in FY2021 (+52.1%).
- Quarterly Operating Expenses has run from a low of $37.84 million in Q3 2021 to a high of $108.14 million in Q3 2025 over five years.
- On a year-over-year basis, Operating Expenses has increased in each of the last seven quarters, with growth averaging 13.0% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q3 2023, with growth of 78.6%; the weakest was Q4 2022, with a decline of 10.6%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $80.87 million (Q1 2026), $89.45 million (Q4 2025) and $108.14 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Texas Pacific Land | 23.55 Bn | 22.38 Bn | - | 54.24 Mn |
| 2 | St Joe | 3.95 Bn | 3.44 Bn | 73.42 Mn | 104.06 Mn |
| 3 | Millrose Properties | 3.88 Bn | 3.52 Bn | - | 29.22 Mn |
| 4 | LandBridge | 2.22 Bn | 2.09 Bn | 65.71 Mn | 15.90 Mn |
| 5 | Opendoor Technologies | 1.99 Bn | -1.83 Bn | 86.00 Mn | 230.00 Mn |
| 6 | Forestar | 1.30 Bn | -43.39 Mn | 84.10 Mn | 38.30 Mn |
| 7 | Five Point Holdings | 662.61 Mn | -795.01 Mn | -23.72 Mn | 21.49 Mn |
| 8 | Tejon Ranch | 437.20 Mn | 356.82 Mn | - | 13.91 Mn |
| 9 | Nam Tai Property | 260.01 Mn | 78.63 Mn | - | - |
| 10 | Global Asset Management | 182.09 Mn | 179.78 Mn | 236,261.00 | 972,259.00 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 104.06 Mn |
| Mar 31, 2026 | 80.87 Mn |
| Dec 31, 2025 | 89.45 Mn |
| Sep 30, 2025 | 108.14 Mn |
| Jun 30, 2025 | 92.12 Mn |
| Mar 31, 2025 | 77.30 Mn |
| Dec 31, 2024 | 78.60 Mn |
| Sep 30, 2024 | 77.74 Mn |
| Jun 30, 2024 | 78.98 Mn |
| Mar 31, 2024 | 71.84 Mn |
| Dec 31, 2023 | 69.43 Mn |
| Sep 30, 2023 | 81.10 Mn |
| Jun 30, 2023 | 86.34 Mn |
| Mar 31, 2023 | 61.69 Mn |
| Dec 31, 2022 | 51.36 Mn |
| Sep 30, 2022 | 45.40 Mn |
| Jun 30, 2022 | 49.45 Mn |
| Mar 31, 2022 | 44.65 Mn |
| Dec 31, 2021 | 57.45 Mn |
| Sep 30, 2021 | 37.84 Mn |
API Access
St Joe 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=JOE&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "JOE", "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=JOE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();