Neighborhood Intelligence (NXH) Shares Outstanding (Diluted) (2010 - 2026)
Neighborhood Intelligence's Shares Outstanding (Diluted) came in at 74.31 million for Q2 2026, up 29.2% from 57.5 million a year earlier and up 7.6% from the prior quarter.
Neighborhood Intelligence (NXH) Shares Outstanding (Diluted) (2010 - 2026) Analysis & Trends
For FY2025, Neighborhood Intelligence's Shares Outstanding (Diluted) was 60.13 million, up 29.2% from FY2024.
- Shares Outstanding (Diluted) has increased in each of the last eight years, with a five-year compound annual growth rate of 7.6% (FY2020 to FY2025).
- Going back by year, Shares Outstanding (Diluted) was 46.54 million in FY2024 (+2.9%), 45.21 million in FY2023 (+2.0%), 44.32 million in FY2022 (+2.3%) and 43.33 million in FY2021 (+4.1%).
- The Q2 2026 figure represents the highest quarterly Shares Outstanding (Diluted) in data going back to Q4 2010.
- Year-over-year, Shares Outstanding (Diluted) has increased for 11 consecutive quarters, with growth averaging 20.8% over the last eight quarters.
- The fastest year-over-year change in Shares Outstanding (Diluted) over five years came in Q3 2025 (growth of 31.8%), and the weakest in Q3 2023 (a decline of 1.1%).
- Business Quant data shows NXH's Shares Outstanding (Diluted) at 69.05 million (Q1 2026), 60.13 million (Q4 2025) and 60.33 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Shares Outstanding (Dil.) (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,712.14 Bn | 2,228.84 Bn | 104.83 Bn | 10.90 Bn |
| 2 | Home Depot | 282.27 Bn | 275.52 Bn | 16.12 Bn | 996.00 Mn |
| 3 | Tjx Companies | 146.16 Bn | 123.70 Bn | 5.07 Bn | 1.12 Bn |
| 4 | Lowes Companies | 101.42 Bn | 94.39 Bn | 8.58 Bn | 560.00 Mn |
| 5 | Ross Stores | 73.06 Bn | 55.98 Bn | 2.12 Bn | 319.45 Mn |
| 6 | Target | 70.86 Bn | 65.45 Bn | 8.94 Bn | 456.60 Mn |
| 7 | Carvana | 70.11 Bn | 61.71 Bn | 1.38 Bn | 739.96 Mn |
| 8 | O Reilly Automotive | 69.29 Bn | 68.38 Bn | 2.52 Bn | 828.88 Mn |
| 9 | Autozone | 45.61 Bn | 44.51 Bn | 2.52 Bn | 16.85 Mn |
| 10 | Neighborhood Intelligence | 225.66 Mn | -351.99 Mn | 96.68 Mn | 74.31 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 74.31 Mn |
| Mar 31, 2026 | 69.05 Mn |
| Dec 31, 2025 | 60.13 Mn |
| Sep 30, 2025 | 60.33 Mn |
| Jun 30, 2025 | 57.50 Mn |
| Mar 31, 2025 | 53.66 Mn |
| Dec 31, 2024 | 46.54 Mn |
| Sep 30, 2024 | 45.77 Mn |
| Jun 30, 2024 | 45.74 Mn |
| Mar 31, 2024 | 45.59 Mn |
| Dec 31, 2023 | 45.21 Mn |
| Sep 30, 2023 | 45.23 Mn |
| Jun 30, 2023 | 45.20 Mn |
| Mar 31, 2023 | 45.07 Mn |
| Dec 31, 2022 | 44.32 Mn |
| Sep 30, 2022 | 45.71 Mn |
| Jun 30, 2022 | 43.16 Mn |
| Mar 31, 2022 | 43.28 Mn |
| Dec 31, 2021 | 43.33 Mn |
| Sep 30, 2021 | 43.32 Mn |
Neighborhood Intelligence Shares Outstanding (Diluted) 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-diluted&ticker=NXH&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "shares-outstanding-diluted", "ticker": "NXH", "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-diluted&ticker=NXH&period=max&api_key=YOUR_API_KEY");
const data = await res.json();