MBody AI (MBAI) EV to EBITDA (2019 - 2023)
MBody AI's (MBAI) EV to EBITDA came in at -0.38 for the quarter ended Sep 30, 2023, compared with -4.66 a year earlier.
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Analysis
MBody AI (MBAI) EV to EBITDA (2019 - 2023) Analysis & Trends
For the trailing twelve months through Sep 30, 2023, EV to EBITDA at MBody AI was -17.44; for the year ended Dec 31, 2022, it was -1.91.
- In prior years, MBody AI's EV to EBITDA was 0.59 in the year ended Dec 31, 2021, -0.30 in the year ended Dec 31, 2020 and 0.19 in the year ended Dec 31, 2019.
- The figure for the quarter ended Sep 30, 2023 stands as the highest quarterly EV to EBITDA since the quarter ended Dec 31, 2021.
- According to Business Quant data, EV to EBITDA for the three prior quarters was -2.27 (quarter ended Jun 30, 2023), -5.47 (quarter ended Mar 31, 2023) and -8.25 (quarter ended Dec 31, 2022).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 260.62 Bn | 239.65 Bn | 4.88 Bn |
| 2 | Abbott Laboratories | 176.70 Bn | 147.13 Bn | 7.27 Bn |
| 3 | Danaher | 167.44 Bn | 151.25 Bn | 3.61 Bn |
| 4 | Intuitive Surgical | 152.30 Bn | 131.72 Bn | 1.96 Bn |
| 5 | Medtronic | 119.73 Bn | 84.98 Bn | 6.34 Bn |
| 6 | Stryker | 115.32 Bn | 101.43 Bn | 4.50 Bn |
| 7 | Boston Scientific | 65.85 Bn | 60.62 Bn | 3.85 Bn |
| 8 | Becton Dickinson | 53.84 Bn | 50.98 Bn | 2.32 Bn |
| 9 | Edwards Lifesciences | 50.96 Bn | 34.97 Bn | 1.35 Bn |
| 10 | MBody AI | 2.38 Mn | 2.16 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2023 | -0.65 |
| Jun 30, 2023 | -3.36 |
| Mar 31, 2023 | -2.97 |
| Dec 31, 2022 | -2.71 |
| Sep 30, 2022 | -1.48 |
| Jun 30, 2022 | -1.80 |
| Mar 31, 2022 | -1.49 |
| Dec 31, 2021 | 1.40 |
| Sep 30, 2021 | -1.65 |
| Jun 30, 2021 | 3.35 |
| Mar 31, 2021 | 4.78 |
| Dec 31, 2020 | 0.35 |
| Sep 30, 2020 | -2.27 |
| Jun 30, 2020 | -1.39 |
| Mar 31, 2020 | 0.10 |
| Dec 31, 2019 | 0.54 |
API Access
MBody 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=MBAI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ev-to-ebitda", "ticker": "MBAI", "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=MBAI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();