Fdctech (FDCT) Operating Expenses (2017 - 2026)
Fdctech (FDCT) recorded Operating Expenses of $4.77 million in Q1 2026, up 94.6% from $2.45 million a year earlier and up 4.7% from the prior quarter.
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Analysis
Fdctech (FDCT) Operating Expenses (2017 - 2026) Analysis & Trends
On a TTM basis, Fdctech's Operating Expenses came in at $15.4 million as of Mar 31, 2026, up 20.1% year-over-year; for FY2025, it was $13.08 million, up 3.2% from FY2024.
- Annual Operating Expenses has increased for five straight years, with a five-year compound annual growth rate of 104.9% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $12.68 million in FY2024 (+171.4%), $4.67 million in FY2023 (+132.4%), $2.01 million in FY2022 (+13.1%) and $1.78 million in FY2021 (+390.5%).
- The Q1 2026 figure is the highest quarterly Operating Expenses in data going back to Q2 2017.
- On a year-over-year basis, Operating Expenses has increased for three consecutive quarters, with growth averaging 112.0% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 581.2% in Q2 2024, against a decline of 32.8% in Q4 2022 at the low end.
- Per Business Quant, the preceding three quarters came in at $4.56 million (Q4 2025), $3.6 million (Q3 2025) and $2.47 million (Q2 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Cme | 106.65 Bn | 94.75 Bn | - | 599.10 Mn |
| 2 | Intercontinental Exchange | 88.81 Bn | 82.54 Bn | - | 1.28 Bn |
| 3 | Robinhood Markets | 88.24 Bn | 69.27 Bn | - | 734.00 Mn |
| 4 | Nasdaq | 53.39 Bn | 50.82 Bn | 1.50 Bn | 788.00 Mn |
| 5 | Interactive Brokers | 37.00 Bn | 14.11 Bn | - | 440.00 Mn |
| 6 | Cboe Global Markets | 33.07 Bn | 24.73 Bn | 731.60 Mn | 255.60 Mn |
| 7 | LPL Financial Holdings | 25.75 Bn | 21.07 Bn | - | 4.67 Bn |
| 8 | Tradeweb Markets | 25.32 Bn | 17.33 Bn | - | 313.68 Mn |
| 9 | Circle Internet | 21.28 Bn | 15.16 Bn | 288.85 Mn | 254.49 Mn |
| 10 | Fdctech | 16.88 Mn | -48.41 Mn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Mar 31, 2026 | 4.77 Mn |
| Dec 31, 2025 | 4.56 Mn |
| Sep 30, 2025 | 3.60 Mn |
| Jun 30, 2025 | 2.47 Mn |
| Mar 31, 2025 | 2.45 Mn |
| Dec 31, 2024 | 3.92 Mn |
| Sep 30, 2024 | 3.14 Mn |
| Jun 30, 2024 | 3.30 Mn |
| Mar 31, 2024 | 2.31 Mn |
| Dec 31, 2023 | 2.39 Mn |
| Sep 30, 2023 | 1.29 Mn |
| Jun 30, 2023 | 485,004.00 |
| Mar 31, 2023 | 512,789.00 |
| Dec 31, 2022 | 530,678.00 |
| Sep 30, 2022 | 394,610.00 |
| Jun 30, 2022 | 526,055.00 |
| Mar 31, 2022 | 558,446.00 |
| Dec 31, 2021 | 789,697.00 |
| Sep 30, 2021 | 492,366.00 |
| Jun 30, 2021 | 276,801.00 |
API Access
Fdctech 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=FDCT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "FDCT", "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=FDCT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();