Lcnb (LCNB) Operating Expenses (2009 - 2026)
Lcnb (LCNB) recorded Operating Expenses of $15.59 million in Q3 2026, up 2.9% from $15.15 million a year earlier but down 0.5% from the prior quarter.
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Analysis
Lcnb (LCNB) Operating Expenses (2009 - 2026) Analysis & Trends
On a TTM basis, Lcnb's Operating Expenses came in at $62.53 million as of Sep 30, 2026, up 2.3% year-over-year; for FY2025, it came in at $61.91 million, down 2.2% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 6.2% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $63.28 million in FY2024 (+16.3%), $54.42 million in FY2023 (+13.1%), $48.13 million in FY2022 (+0.2%) and $48.04 million in FY2021 (+4.9%).
- Quarterly Operating Expenses has ranged from $11.47 million in Q2 2022 to $17.83 million in Q2 2024 over the past five years.
- On a year-over-year basis, Operating Expenses has increased for four consecutive quarters, with an average decline of 2.4% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 47.6% in Q2 2024, against a decline of 17.0% in Q4 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at $15.68 million (Q2 2026), $15.88 million (Q1 2026) and $15.39 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 909.02 Bn | 886.77 Bn | - | 27.30 Bn |
| 2 | Banco Santander Chile | 406.67 Bn | -7,110.43 Bn | - | - |
| 3 | Bank Of America | 350.91 Bn | -2,025.20 Bn | - | 19.72 Bn |
| 4 | Hsbc Holdings | 308.71 Bn | -2,966.46 Bn | - | 8.82 Bn |
| 5 | Morgan Stanley | 293.66 Bn | -249.15 Bn | - | 13.71 Bn |
| 6 | Royal Bank Of Canada | 283.56 Bn | -546.44 Bn | - | 7.02 Bn |
| 7 | Goldman Sachs | 262.71 Bn | -3,480.74 Bn | - | 11.31 Bn |
| 8 | Wells Fargo & Company | 257.44 Bn | 92.87 Bn | - | 13.74 Bn |
| 9 | Mitsubishi Ufj Financial | 256.82 Bn | -75.42 Bn | 10.89 Bn | 17.50 Bn |
| 10 | Lcnb | 280.39 Mn | 134.49 Mn | - | 15.59 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 15.59 Mn |
| Jun 30, 2026 | 15.68 Mn |
| Mar 31, 2026 | 15.88 Mn |
| Dec 31, 2025 | 15.39 Mn |
| Sep 30, 2025 | 15.15 Mn |
| Jun 30, 2025 | 15.57 Mn |
| Mar 31, 2025 | 15.81 Mn |
| Dec 31, 2024 | 14.59 Mn |
| Sep 30, 2024 | 15.39 Mn |
| Jun 30, 2024 | 17.83 Mn |
| Mar 31, 2024 | 15.47 Mn |
| Dec 31, 2023 | 17.58 Mn |
| Sep 30, 2023 | 12.24 Mn |
| Jun 30, 2023 | 12.08 Mn |
| Mar 31, 2023 | 12.53 Mn |
| Dec 31, 2022 | 12.07 Mn |
| Sep 30, 2022 | 12.35 Mn |
| Jun 30, 2022 | 11.47 Mn |
| Mar 31, 2022 | 12.25 Mn |
| Dec 31, 2021 | 12.31 Mn |
API Access
Lcnb 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=LCNB&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "LCNB", "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=LCNB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();