Network-1 Technologies (NTIP) Shares Outstanding (2010 - 2026)
Network-1 Technologies' Shares Outstanding came in at 22.84 million for Q2 2026, down 0.2% from 22.87 million a year earlier but up 0.1% from the prior quarter.
Network-1 Technologies (NTIP) Shares Outstanding (2010 - 2026) Analysis & Trends
For FY2025, Network-1 Technologies' Shares Outstanding was 22.85 million, down 1.7% from FY2024.
- Shares Outstanding has declined in each of the last four years, with a five-year compound annual growth rate of -1.0% (FY2020 to FY2025).
- Going back by year, Shares Outstanding was 23.25 million in FY2024 (-2.3%), 23.79 million in FY2023 (-0.1%), 23.83 million in FY2022 (-1.3%) and 24.14 million in FY2021 (+0.5%).
- The five-year range for quarterly Shares Outstanding is 22.81 million (Q3 2025) to 24.14 million (Q4 2021).
- Year-over-year, Shares Outstanding has declined for 11 consecutive quarters, with an average decline of 1.7% over the last eight quarters.
- The fastest year-over-year change in Shares Outstanding over five years came in Q4 2021 (growth of 0.5%), and the weakest in Q3 2024 (a decline of 2.8%).
- Business Quant data shows NTIP's Shares Outstanding at 22.81 million (Q1 2026), 22.85 million (Q4 2025) and 22.81 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Shares Outstanding (Qtr) |
|---|---|---|---|---|---|
| 1 | Nvidia | 5,369.70 Bn | 5,143.86 Bn | 72.14 Bn | 24.19 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 2,240.62 Bn | 1,865.48 Bn | 27.22 Bn | 5.19 Bn |
| 3 | Broadcom | 1,610.24 Bn | 1,536.29 Bn | 20.46 Bn | 4.77 Bn |
| 4 | Micron Technology | 1,032.70 Bn | 938.34 Bn | 47.05 Bn | 1.13 Bn |
| 5 | Advanced Micro Devices | 903.31 Bn | 860.06 Bn | 6.20 Bn | 1.63 Bn |
| 6 | Asml Holding | 651.41 Bn | 607.10 Bn | 5.90 Bn | 388.50 Mn |
| 7 | Intel | 474.60 Bn | 343.73 Bn | 6.51 Bn | 5.10 Bn |
| 8 | Lam Research | 327.65 Bn | 304.45 Bn | 3.48 Bn | 1.26 Bn |
| 9 | Applied Materials | 324.38 Bn | 289.82 Bn | 4.59 Bn | 794.00 Mn |
| 10 | Network-1 Technologies | 36.08 Mn | -106.23 Mn | - | 22.84 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 22.84 Mn |
| Mar 31, 2026 | 22.81 Mn |
| Dec 31, 2025 | 22.85 Mn |
| Sep 30, 2025 | 22.81 Mn |
| Jun 30, 2025 | 22.87 Mn |
| Mar 31, 2025 | 22.91 Mn |
| Dec 31, 2024 | 23.25 Mn |
| Sep 30, 2024 | 23.13 Mn |
| Jun 30, 2024 | 23.30 Mn |
| Mar 31, 2024 | 23.54 Mn |
| Dec 31, 2023 | 23.79 Mn |
| Sep 30, 2023 | 23.80 Mn |
| Jun 30, 2023 | 23.80 Mn |
| Mar 31, 2023 | 23.87 Mn |
| Dec 31, 2022 | 23.83 Mn |
| Sep 30, 2022 | 23.77 Mn |
| Jun 30, 2022 | 23.85 Mn |
| Mar 31, 2022 | 23.91 Mn |
| Dec 31, 2021 | 24.14 Mn |
| Sep 30, 2021 | 23.93 Mn |
Network-1 Technologies Shares Outstanding 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=shares-outstanding&ticker=NTIP&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "shares-outstanding", "ticker": "NTIP", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=shares-outstanding&ticker=NTIP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();