MBody AI (MBAI) Pension (2012 - 2015)
MBody AI (MBAI) posted Pension of $980,000 for the quarter ended Sep 30, 2015, up 51.2% from the prior quarter.
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Analysis
MBody AI (MBAI) Pension (2012 - 2015) Analysis & Trends
As of Dec 31, 2014, MBody AI's Pension came in at $1.12 million, up 70.5% from the prior year.
- In prior years, MBody AI's Pension was $658,000 in the year ended Dec 31, 2013 (+29.3%) and $509,000 in the year ended Dec 31, 2012.
- Quarterly Pension has run from a low of $648,000 in the quarter ended Jun 30, 2015 to a high of $1.12 million in the quarter ended Dec 31, 2014 over five years.
- According to Business Quant data, Pension for the three prior quarters was $648,000 (quarter ended Jun 30, 2015), $759,000 (quarter ended Mar 31, 2015) and $1.12 million (quarter ended Dec 31, 2014).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 256.92 Bn | 235.95 Bn | 4.88 Bn |
| 2 | Abbott Laboratories | 173.58 Bn | 144.01 Bn | 7.27 Bn |
| 3 | Danaher | 162.23 Bn | 146.04 Bn | 3.61 Bn |
| 4 | Intuitive Surgical | 149.63 Bn | 129.06 Bn | 1.96 Bn |
| 5 | Medtronic | 120.11 Bn | 85.36 Bn | 6.34 Bn |
| 6 | Stryker | 113.85 Bn | 99.96 Bn | 4.50 Bn |
| 7 | Boston Scientific | 65.44 Bn | 60.21 Bn | 3.85 Bn |
| 8 | Becton Dickinson | 53.40 Bn | 50.54 Bn | 2.32 Bn |
| 9 | Edwards Lifesciences | 50.59 Bn | 34.60 Bn | 1.35 Bn |
| 10 | MBody AI | 2.10 Mn | 1.88 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2015 | 980,000.00 |
| Jun 30, 2015 | 648,000.00 |
| Mar 31, 2015 | 759,000.00 |
| Dec 31, 2014 | 1.12 Mn |
| Dec 31, 2013 | 658,000.00 |
| Dec 31, 2012 | 509,000.00 |
API Access
MBody AI Pension 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=pension&ticker=MBAI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "pension", "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=pension&ticker=MBAI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();