Quaint Oak Bancorp (QNTO) Operating Expenses (2011 - 2026)
Quaint Oak Bancorp's Operating Expenses came in at $5.65 million for Q2 2026, up 2.0% from $5.53 million a year earlier but down 7.8% from the prior quarter.
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Analysis
Quaint Oak Bancorp (QNTO) Operating Expenses (2011 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Quaint Oak Bancorp reported Operating Expenses of $23.89 million, up 9.9% year-over-year; for FY2025, it was $23.2 million, up 10.4% from FY2024.
- Operating Expenses carries a five-year compound annual growth rate of 13.9% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $21.02 million in FY2024 (+0.5%), $20.92 million in FY2023 (-23.3%), $27.26 million in FY2022 (+29.3%) and $21.09 million in FY2021 (+73.9%).
- The five-year range for quarterly Operating Expenses is $4.92 million (Q3 2024) to $7.32 million (Q3 2022).
- Year-over-year, Operating Expenses has increased for seven consecutive quarters, with growth averaging 6.9% over the last eight quarters.
- The fastest year-over-year change in Operating Expenses over five years came in Q4 2021 (growth of 76.5%), and the weakest in Q3 2023 (a decline of 29.7%).
- Business Quant data shows QNTO's Operating Expenses at $6.12 million (Q1 2026), $6.4 million (Q4 2025) and $5.73 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
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 | Quaint Oak Bancorp | 38.97 Mn | -160.71 Mn | - | 5.65 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 5.65 Mn |
| Mar 31, 2026 | 6.12 Mn |
| Dec 31, 2025 | 6.40 Mn |
| Sep 30, 2025 | 5.73 Mn |
| Jun 30, 2025 | 5.53 Mn |
| Mar 31, 2025 | 5.54 Mn |
| Dec 31, 2024 | 5.73 Mn |
| Sep 30, 2024 | 4.92 Mn |
| Jun 30, 2024 | 5.24 Mn |
| Mar 31, 2024 | 5.13 Mn |
| Dec 31, 2023 | 5.43 Mn |
| Sep 30, 2023 | 5.15 Mn |
| Jun 30, 2023 | 5.29 Mn |
| Mar 31, 2023 | 5.31 Mn |
| Dec 31, 2022 | 7.17 Mn |
| Sep 30, 2022 | 7.32 Mn |
| Jun 30, 2022 | 6.59 Mn |
| Mar 31, 2022 | 6.18 Mn |
| Dec 31, 2021 | 6.11 Mn |
| Sep 30, 2021 | 5.43 Mn |
API Access
Quaint Oak 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=QNTO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "QNTO", "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=QNTO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();