Chemung Financial (CHMG) Operating Expenses (2010 - 2026)
Chemung Financial (CHMG) posted Operating Expenses of $19.32 million for Q2 2026, up 8.7% from $17.77 million a year earlier and up 10.6% from the prior quarter.
Chemung Financial (CHMG) Operating Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Chemung Financial was $72.82 million, up 5.5% year-over-year; for FY2025, it was $70.73 million, up 5.2% from FY2024.
- Annual Operating Expenses has increased for four consecutive years, with a five-year compound annual growth rate of 4.8% (FY2020 to FY2025).
- In prior years, Chemung Financial's Operating Expenses was $67.25 million in FY2024 (+4.7%), $64.24 million in FY2023 (+8.4%), $59.28 million in FY2022 (+6.5%) and $55.68 million in FY2021 (-0.5%).
- The Q2 2026 figure stands as the highest quarterly Operating Expenses in data going back to Q2 2010.
- On a year-over-year basis, Operating Expenses has increased in each of the last 18 quarters, with growth averaging 5.5% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q2 2023, with growth of 11.0%; the weakest was Q4 2021, with a decline of 7.8%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $17.46 million (Q1 2026), $18.39 million (Q4 2025) and $17.65 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 895.36 Bn | 924.83 Bn | - | 27.32 Bn |
| 2 | Banco Santander Chile | 425.01 Bn | 544.95 Bn | - | -3,218.32 Bn |
| 3 | Bank Of America | 389.22 Bn | -1,986.85 Bn | - | 18.63 Bn |
| 4 | Hsbc Holdings | 347.56 Bn | 347.61 Bn | - | - |
| 5 | Morgan Stanley | 304.44 Bn | -204.66 Bn | - | 13.90 Bn |
| 6 | Royal Bank Of Canada | 281.54 Bn | 132.29 Bn | - | 7.02 Bn |
| 7 | Mitsubishi Ufj Financial | 277.23 Bn | -1,311.26 Bn | 10.89 Bn | 17.50 Bn |
| 8 | Goldman Sachs | 267.12 Bn | -3,289.99 Bn | - | 11.67 Bn |
| 9 | Wells Fargo & Company | 244.76 Bn | 246.90 Bn | - | 13.66 Bn |
| 10 | Chemung Financial | 394.06 Mn | 109.83 Mn | - | 19.32 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 19.32 Mn |
| Mar 31, 2026 | 17.46 Mn |
| Dec 31, 2025 | 18.39 Mn |
| Sep 30, 2025 | 17.65 Mn |
| Jun 30, 2025 | 17.77 Mn |
| Mar 31, 2025 | 16.93 Mn |
| Dec 31, 2024 | 17.82 Mn |
| Sep 30, 2024 | 16.51 Mn |
| Jun 30, 2024 | 16.22 Mn |
| Mar 31, 2024 | 16.70 Mn |
| Dec 31, 2023 | 16.83 Mn |
| Sep 30, 2023 | 15.67 Mn |
| Jun 30, 2023 | 15.91 Mn |
| Mar 31, 2023 | 15.84 Mn |
| Dec 31, 2022 | 15.69 Mn |
| Sep 30, 2022 | 14.58 Mn |
| Jun 30, 2022 | 14.34 Mn |
| Mar 31, 2022 | 14.67 Mn |
| Dec 31, 2021 | 14.38 Mn |
| Sep 30, 2021 | 14.10 Mn |
Chemung Financial 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=CHMG&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "CHMG", "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=CHMG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();