Siebert Financial (SIEB) Operating Expenses (2010 - 2026)
Siebert Financial (SIEB) reported Operating Expenses of $31.65 million for Q2 2026, up 52.8% from $20.71 million a year earlier and up 20.2% from the prior quarter.
Siebert Financial (SIEB) Operating Expenses (2010 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Siebert Financial's Operating Expenses came in at $107.49 million, up 43.5% year-over-year; for FY2025, it came in at $88.64 million, up 33.4% from FY2024.
- Operating Expenses has increased for three consecutive years, with a five-year compound annual growth rate of 11.4% (FY2020 to FY2025).
- By year, Operating Expenses came in at $66.43 million in FY2024 (+24.4%), $53.39 million in FY2023 (+7.5%), $49.66 million in FY2022 (-18.5%) and $60.93 million in FY2021 (+17.9%).
- The Q2 2026 figure ranks as the highest quarterly Operating Expenses in data going back to Q2 2010.
- Year over year, Operating Expenses has now increased in each of the last 13 quarters, with growth averaging 34.8% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was Q2 2026 (growth of 52.8%); the low point was Q1 2022 (a decline of 25.3%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $26.34 million (Q1 2026), $24.85 million (Q4 2025) and $24.66 million (Q3 2025).
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 | Siebert Financial | 76.63 Mn | -71.37 Mn | - | 31.65 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 31.65 Mn |
| Mar 31, 2026 | 26.34 Mn |
| Dec 31, 2025 | 24.85 Mn |
| Sep 30, 2025 | 24.66 Mn |
| Jun 30, 2025 | 20.71 Mn |
| Mar 31, 2025 | 18.42 Mn |
| Dec 31, 2024 | 18.07 Mn |
| Sep 30, 2024 | 17.72 Mn |
| Jun 30, 2024 | 15.28 Mn |
| Mar 31, 2024 | 15.35 Mn |
| Dec 31, 2023 | 14.82 Mn |
| Sep 30, 2023 | 13.78 Mn |
| Jun 30, 2023 | 12.93 Mn |
| Mar 31, 2023 | 11.86 Mn |
| Dec 31, 2022 | 12.78 Mn |
| Sep 30, 2022 | 12.75 Mn |
| Jun 30, 2022 | 12.25 Mn |
| Mar 31, 2022 | 11.88 Mn |
| Dec 31, 2021 | 14.22 Mn |
| Sep 30, 2021 | 15.92 Mn |
Siebert 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=SIEB&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SIEB", "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=SIEB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();