Wilco 63 (WLCO) Accumulated Expenses (2026)
Analysis
Wilco 63 (WLCO) Accumulated Expenses (2026) Analysis & Trends
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Cme | 110.48 Bn | 98.81 Bn | 359.20 Mn |
| 2 | Bank of New York Mellon | 101.69 Bn | 35.78 Bn | - |
| 3 | Intercontinental Exchange | 98.41 Bn | 92.22 Bn | 1.22 Bn |
| 4 | Robinhood Markets | 73.28 Bn | 52.89 Bn | - |
| 5 | Nasdaq | 61.44 Bn | 58.88 Bn | 1.48 Bn |
| 6 | State Street | 46.84 Bn | 43.46 Bn | - |
| 7 | Cboe Global Markets | 38.04 Bn | 28.52 Bn | 712.20 Mn |
| 8 | Interactive Brokers | 35.16 Bn | 18.81 Bn | - |
| 9 | Northern Trust | 32.22 Bn | 32.22 Bn | - |
| 10 | Wilco 63 | 282.61 Mn | 282.32 Mn | - |
API Access
Wilco 63 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=WLCO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "WLCO", "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=WLCO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();