Neuroone Medical Technologies (NMTC) Other Operating Expenses (2012 - 2023)
Neuroone Medical Technologies' Other Operating Expenses came in at $237,007 for fiscal Q3 2023 (quarter ended Jun 30, 2023), up 12.1% from $211,472 a year earlier and up 18.8% from the prior quarter.
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Analysis
Neuroone Medical Technologies (NMTC) Other Operating Expenses (2012 - 2023) Analysis & Trends
For FY2013 (ended Dec 31, 2013), Neuroone Medical Technologies' Other Operating Expenses was $24,853, up 107.1% from FY2012.
- Going back by fiscal year, Other Operating Expenses was $11,998 in FY2012.
- The fiscal Q3 2023 figure represents the highest quarterly Other Operating Expenses in data going back to fiscal Q4 2012.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 249.71 Bn | 228.86 Bn | 4.88 Bn |
| 2 | Abbott Laboratories | 171.00 Bn | 142.08 Bn | 7.27 Bn |
| 3 | Danaher | 155.79 Bn | 139.61 Bn | 3.61 Bn |
| 4 | Intuitive Surgical | 143.91 Bn | 123.46 Bn | 1.96 Bn |
| 5 | Medtronic | 110.42 Bn | 76.29 Bn | 6.34 Bn |
| 6 | Stryker | 105.71 Bn | 91.82 Bn | 4.50 Bn |
| 7 | Boston Scientific | 63.26 Bn | 58.27 Bn | 3.85 Bn |
| 8 | Edwards Lifesciences | 49.80 Bn | 33.91 Bn | 1.35 Bn |
| 9 | Becton Dickinson | 48.78 Bn | 45.93 Bn | 2.32 Bn |
| 10 | Neuroone Medical Technologies | 8.96 Mn | -6.06 Mn | 1.18 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2023 | 237,007.00 |
| Mar 31, 2023 | 199,467.00 |
| Jun 30, 2022 | 211,472.00 |
| Mar 31, 2022 | 194,874.00 |
| Sep 30, 2016 | 2,889.00 |
| Mar 31, 2015 | 67.00 |
| Mar 31, 2014 | 3,875.00 |
| Dec 31, 2013 | 24,853.00 |
| Dec 31, 2012 | 11,998.00 |
API Access
Neuroone Medical Technologies Other Operating 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=other-operating-expenses&ticker=NMTC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-operating-expenses", "ticker": "NMTC", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=other-operating-expenses&ticker=NMTC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();