Evercore (EVR) Operating Expenses (2010 - 2026)
Evercore (EVR) posted Operating Expenses of $843.62 million for Q2 2026, up 23.4% from $683.44 million a year earlier but down 20.5% from the prior quarter.
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Analysis
Evercore (EVR) Operating Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Evercore was $3.7 billion, up 40.2% year-over-year; for FY2025, it was $3.07 billion, up 25.0% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of 12.0% (FY2020 to FY2025).
- In prior years, Evercore's Operating Expenses was $2.45 billion in FY2024 (+18.7%), $2.07 billion in FY2023 (unchanged), $2.07 billion in FY2022 (-5.5%) and $2.19 billion in FY2021 (+25.9%).
- Quarterly Operating Expenses has run from a low of $441.7 million in Q2 2023 to a high of $1.06 billion in Q1 2026 over five years.
- On a year-over-year basis, Operating Expenses has increased in each of the last 12 quarters, with growth averaging 30.2% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q1 2026, with growth of 81.8%; the weakest was Q3 2022, with a decline of 22.8%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $1.06 billion (Q1 2026), $976.11 million (Q4 2025) and $822.68 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Cme | 106.56 Bn | 94.66 Bn | - | 599.10 Mn |
| 2 | Intercontinental Exchange | 89.45 Bn | 83.19 Bn | - | 1.28 Bn |
| 3 | Robinhood Markets | 88.18 Bn | 69.22 Bn | - | 734.00 Mn |
| 4 | Nasdaq | 53.47 Bn | 50.90 Bn | 1.50 Bn | 788.00 Mn |
| 5 | Interactive Brokers | 37.14 Bn | 14.26 Bn | - | 440.00 Mn |
| 6 | Cboe Global Markets | 33.00 Bn | 24.66 Bn | 731.60 Mn | 255.60 Mn |
| 7 | LPL Financial Holdings | 25.71 Bn | 21.03 Bn | - | 4.67 Bn |
| 8 | Tradeweb Markets | 25.33 Bn | 17.34 Bn | - | 313.68 Mn |
| 9 | Circle Internet | 21.30 Bn | 15.18 Bn | 288.85 Mn | 254.49 Mn |
| 10 | Evercore | 9.73 Bn | -119.28 Mn | - | 843.62 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 843.62 Mn |
| Mar 31, 2026 | 1.06 Bn |
| Dec 31, 2025 | 976.11 Mn |
| Sep 30, 2025 | 822.68 Mn |
| Jun 30, 2025 | 683.44 Mn |
| Mar 31, 2025 | 583.65 Mn |
| Dec 31, 2024 | 762.77 Mn |
| Sep 30, 2024 | 612.23 Mn |
| Jun 30, 2024 | 580.98 Mn |
| Mar 31, 2024 | 496.70 Mn |
| Dec 31, 2023 | 666.48 Mn |
| Sep 30, 2023 | 493.39 Mn |
| Jun 30, 2023 | 441.70 Mn |
| Mar 31, 2023 | 465.24 Mn |
| Dec 31, 2022 | 621.24 Mn |
| Sep 30, 2022 | 446.54 Mn |
| Jun 30, 2022 | 484.74 Mn |
| Mar 31, 2022 | 513.49 Mn |
| Dec 31, 2021 | 659.71 Mn |
| Sep 30, 2021 | 578.40 Mn |
API Access
Evercore 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=EVR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "EVR", "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=EVR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();