Home Bancorp (HBCP) Operating Expenses (2010 - 2026)
Home Bancorp (HBCP) recorded Operating Expenses of $24.55 million in Q2 2026, up 9.6% from $22.41 million a year earlier and up 7.0% from the prior quarter.
Home Bancorp (HBCP) Operating Expenses (2010 - 2026) Analysis & Trends
On a TTM basis, Home Bancorp's Operating Expenses came in at $93.07 million as of Jun 30, 2026, up 5.0% year-over-year; for FY2025, it came in at $89.56 million, up 2.6% from FY2024.
- Annual Operating Expenses has increased for five straight years, with a five-year compound annual growth rate of 7.3% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $87.29 million in FY2024 (+5.4%), $82.84 million in FY2023 (+1.1%), $81.91 million in FY2022 (+22.3%) and $66.98 million in FY2021 (+6.4%).
- The Q2 2026 figure is the highest quarterly Operating Expenses in data going back to Q2 2010.
- On a year-over-year basis, Operating Expenses has increased for ten consecutive quarters, with growth averaging 4.9% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 31.4% in Q2 2022, against a decline of 3.7% in Q2 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $22.94 million (Q1 2026), $23.05 million (Q4 2025) and $22.53 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 890.60 Bn | 920.07 Bn | - | 27.32 Bn |
| 2 | Banco Santander Chile | 421.74 Bn | 541.68 Bn | - | -3,218.32 Bn |
| 3 | Bank Of America | 385.85 Bn | -1,990.22 Bn | - | 18.63 Bn |
| 4 | Hsbc Holdings | 345.94 Bn | 345.99 Bn | - | - |
| 5 | Morgan Stanley | 303.15 Bn | -205.95 Bn | - | 13.90 Bn |
| 6 | Royal Bank Of Canada | 279.82 Bn | 130.57 Bn | - | 7.02 Bn |
| 7 | Mitsubishi Ufj Financial | 274.62 Bn | -1,313.87 Bn | 10.89 Bn | 17.50 Bn |
| 8 | Goldman Sachs | 267.07 Bn | -3,290.04 Bn | - | 11.67 Bn |
| 9 | Wells Fargo & Company | 243.79 Bn | 245.93 Bn | - | 13.66 Bn |
| 10 | Home Bancorp | 523.15 Mn | 523.15 Mn | - | 24.55 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 24.55 Mn |
| Mar 31, 2026 | 22.94 Mn |
| Dec 31, 2025 | 23.05 Mn |
| Sep 30, 2025 | 22.53 Mn |
| Jun 30, 2025 | 22.41 Mn |
| Mar 31, 2025 | 21.58 Mn |
| Dec 31, 2024 | 22.36 Mn |
| Sep 30, 2024 | 22.26 Mn |
| Jun 30, 2024 | 21.81 Mn |
| Mar 31, 2024 | 20.87 Mn |
| Dec 31, 2023 | 20.60 Mn |
| Sep 30, 2023 | 21.34 Mn |
| Jun 30, 2023 | 20.96 Mn |
| Mar 31, 2023 | 19.94 Mn |
| Dec 31, 2022 | 21.18 Mn |
| Sep 30, 2022 | 20.72 Mn |
| Jun 30, 2022 | 21.77 Mn |
| Mar 31, 2022 | 18.24 Mn |
| Dec 31, 2021 | 18.02 Mn |
| Sep 30, 2021 | 16.43 Mn |
Home Bancorp 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=HBCP&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "HBCP", "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=HBCP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();