Simmons First National (SFNC) Shares Outstanding (2010 - 2026)
Simmons First National's Shares Outstanding came in at 144.88 million for Q2 2026, up 15.0% from 125.96 million a year earlier and unchanged from the prior quarter.
Simmons First National (SFNC) Shares Outstanding (2010 - 2026) Analysis & Trends
For FY2025, Simmons First National's Shares Outstanding was 134.25 million, up 7.0% from FY2024.
- Shares Outstanding carries a five-year compound annual growth rate of 4.1% (FY2020 to FY2025).
- Going back by year, Shares Outstanding was 125.49 million in FY2024 (-0.7%), 126.34 million in FY2023 (+1.9%), 123.96 million in FY2022 (+13.1%) and 109.58 million in FY2021 (-0.3%).
- The five-year range for quarterly Shares Outstanding is 107.82 million (Q3 2021) to 144.9 million (Q1 2026).
- Year-over-year, Shares Outstanding has increased for six consecutive quarters, with growth averaging 6.1% over the last eight quarters.
- The fastest year-over-year change in Shares Outstanding over five years came in Q3 2022 (growth of 18.6%), and the weakest in Q3 2023 (a decline of 1.5%).
- Business Quant data shows SFNC's Shares Outstanding at 144.9 million (Q1 2026), 134.25 million (Q4 2025) and 140.23 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Shares Outstanding (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 879.54 Bn | 909.01 Bn | - | 2.69 Bn |
| 2 | Banco Santander Chile | 418.48 Bn | 538.42 Bn | - | 26.92 Bn |
| 3 | Bank Of America | 381.92 Bn | -1,994.15 Bn | - | 7.15 Bn |
| 4 | Hsbc Holdings | 341.10 Bn | 341.15 Bn | - | 3.49 Bn |
| 5 | Morgan Stanley | 295.71 Bn | -213.38 Bn | - | 1.55 Bn |
| 6 | Royal Bank Of Canada | 275.38 Bn | 126.13 Bn | - | 1.41 Bn |
| 7 | Mitsubishi Ufj Financial | 273.79 Bn | -1,314.70 Bn | 10.89 Bn | 11.40 Bn |
| 8 | Goldman Sachs | 262.78 Bn | -3,294.34 Bn | - | 300.10 Mn |
| 9 | Wells Fargo & Company | 242.61 Bn | 244.75 Bn | - | 3.04 Bn |
| 10 | Simmons First National | 3.26 Bn | 3.21 Bn | - | 144.88 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 144.88 Mn |
| Mar 31, 2026 | 144.90 Mn |
| Dec 31, 2025 | 134.25 Mn |
| Sep 30, 2025 | 140.23 Mn |
| Jun 30, 2025 | 125.96 Mn |
| Mar 31, 2025 | 125.80 Mn |
| Dec 31, 2024 | 125.49 Mn |
| Sep 30, 2024 | 125.54 Mn |
| Jun 30, 2024 | 125.47 Mn |
| Mar 31, 2024 | 125.34 Mn |
| Dec 31, 2023 | 126.34 Mn |
| Sep 30, 2023 | 125.91 Mn |
| Jun 30, 2023 | 127.10 Mn |
| Mar 31, 2023 | 127.19 Mn |
| Dec 31, 2022 | 123.96 Mn |
| Sep 30, 2022 | 127.88 Mn |
| Jun 30, 2022 | 128.31 Mn |
| Mar 31, 2022 | 112.44 Mn |
| Dec 31, 2021 | 109.58 Mn |
| Sep 30, 2021 | 107.82 Mn |
Simmons First National 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=SFNC&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "shares-outstanding", "ticker": "SFNC", "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=SFNC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();