Timberland Bancorp (TSBK) Operating Expenses (2010 - 2026)
Timberland Bancorp's Operating Expenses came in at $11.64 million for fiscal Q3 2026 (quarter ended Jun 30, 2026), up 4.2% from $11.17 million a year earlier but down 0.2% from the prior quarter.
Timberland Bancorp (TSBK) Operating Expenses (2010 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Timberland Bancorp reported Operating Expenses of $46.69 million, up 4.9% year-over-year; for FY2025 (ended Sep 30, 2025), it came in at $45.39 million, up 3.8% from FY2024.
- Operating Expenses has increased in each of the last five fiscal years, with a five-year compound annual growth rate of 5.9% (FY2020 to FY2025).
- Going back by fiscal year, Operating Expenses was $43.75 million in FY2024 (+0.9%), $43.37 million in FY2023 (+12.3%), $38.63 million in FY2022 (+11.7%) and $34.59 million in FY2021 (+1.6%).
- The five-year range for quarterly Operating Expenses is $9.02 million (fiscal Q4 2021) to $11.96 million (fiscal Q4 2025).
- Year-over-year, Operating Expenses has increased for 20 consecutive quarters, with growth averaging 3.4% over the last eight quarters.
- Over the past five years, the year-over-year growth in Operating Expenses ranged from 0.4% (fiscal Q2 2024) to 17.3% (fiscal Q2 2023).
- Business Quant data shows TSBK's Operating Expenses at $11.66 million (Q2 2026), $11.43 million (Q1 2026) and $11.96 million (Q4 2025) in the three fiscal quarters before Q3 2026.
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 | Timberland Bancorp | 348.70 Mn | -709.97 Mn | - | 11.64 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 11.64 Mn |
| Mar 31, 2026 | 11.66 Mn |
| Dec 31, 2025 | 11.43 Mn |
| Sep 30, 2025 | 11.96 Mn |
| Jun 30, 2025 | 11.17 Mn |
| Mar 31, 2025 | 11.19 Mn |
| Dec 31, 2024 | 11.07 Mn |
| Sep 30, 2024 | 11.06 Mn |
| Jun 30, 2024 | 11.07 Mn |
| Mar 31, 2024 | 10.99 Mn |
| Dec 31, 2023 | 10.62 Mn |
| Sep 30, 2023 | 10.97 Mn |
| Jun 30, 2023 | 10.93 Mn |
| Mar 31, 2023 | 10.94 Mn |
| Dec 31, 2022 | 10.54 Mn |
| Sep 30, 2022 | 10.16 Mn |
| Jun 30, 2022 | 9.87 Mn |
| Mar 31, 2022 | 9.33 Mn |
| Dec 31, 2021 | 9.26 Mn |
| Sep 30, 2021 | 9.02 Mn |
Timberland 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=TSBK&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "TSBK", "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=TSBK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();