Fabric.AI (FABC) EV to EBITDA (2013)
Fabric.AI's EV to EBITDA came in at 1048431.20 for Q4 2013.
Analysis
Fabric.AI (FABC) EV to EBITDA (2013) Analysis & Trends
For FY2013, Fabric.AI's EV to EBITDA was 708779.57.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Robinhood Markets | 104.70 Bn | 85.79 Bn | - |
| 2 | Bank of New York Mellon | 100.72 Bn | 40.09 Bn | - |
| 3 | Cme | 94.58 Bn | 94.58 Bn | - |
| 4 | Intercontinental Exchange | 85.83 Bn | 79.63 Bn | - |
| 5 | Nasdaq | 52.05 Bn | 49.49 Bn | 1.50 Bn |
| 6 | State Street | 49.39 Bn | 49.39 Bn | - |
| 7 | Interactive Brokers | 39.24 Bn | 32.69 Bn | - |
| 8 | Northern Trust | 31.94 Bn | 31.94 Bn | - |
| 9 | Cboe Global Markets | 26.47 Bn | 18.13 Bn | 731.60 Mn |
| 10 | Fabric.AI | 9.77 Mn | -39.10 Mn | - |
API Access
Fabric.AI EV to EBITDA 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=ev-to-ebitda&ticker=FABC&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ev-to-ebitda", "ticker": "FABC", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=ev-to-ebitda&ticker=FABC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();