BingEx (FLX) Accumulated Expenses (2023 - 2026)
BingEx (FLX) posted Accumulated Expenses of $17.24 million for the quarter ended Jun 30, 2026, down 7.6% from $18.66 million a year earlier and down 2.7% from the prior quarter.
BingEx (FLX) Accumulated Expenses (2023 - 2026) Analysis & Trends
As of Dec 31, 2025, BingEx's Accumulated Expenses came in at $20.85 million, down 8.2% from the prior year.
- In prior years, BingEx's Accumulated Expenses was $22.71 million in the year ended Dec 31, 2024 (-35.6%) and $35.28 million in the year ended Dec 31, 2023.
- The figure for the quarter ended Jun 30, 2026 stands as the lowest quarterly Accumulated Expenses in data going back to the quarter ended Dec 31, 2023.
- On a year-over-year basis, Accumulated Expenses has declined in each of the last four quarters, with an average decline of 15.0% over the last five quarters.
- According to Business Quant data, Accumulated Expenses for the three prior quarters was $17.72 million (quarter ended Mar 31, 2026), $20.56 million (quarter ended Dec 31, 2025) and $18.74 million (quarter ended Sep 30, 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Union Pacific | 161.62 Bn | 156.15 Bn | - |
| 2 | Csx | 86.16 Bn | 82.37 Bn | - |
| 3 | Canadian Pacific Kansas City | 74.78 Bn | 74.50 Bn | - |
| 4 | United Parcel Service | 70.01 Bn | 46.94 Bn | - |
| 5 | Norfolk Southern | 69.45 Bn | 64.09 Bn | - |
| 6 | Fedex | 67.46 Bn | 33.40 Bn | - |
| 7 | Delta Air Lines | 54.88 Bn | 37.06 Bn | - |
| 8 | Old Dominion Freight Line | 36.07 Bn | 35.33 Bn | - |
| 9 | Ryanair Holdings | 28.71 Bn | 12.72 Bn | 3.13 Bn |
| 10 | BingEx | 106.04 Mn | -380.41 Mn | 14.08 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 17.24 Mn |
| Mar 31, 2026 | 17.72 Mn |
| Dec 31, 2025 | 20.56 Mn |
| Sep 30, 2025 | 18.74 Mn |
| Jun 30, 2025 | 18.66 Mn |
| Mar 31, 2025 | 18.35 Mn |
| Dec 31, 2024 | 23.07 Mn |
| Sep 30, 2024 | 23.28 Mn |
| Dec 31, 2023 | 34.63 Mn |
BingEx Accumulated 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=accumulated-expenses&ticker=FLX&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "FLX", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=FLX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();