Portland General Electric (POR) Weighted Average Shares Outstanding (2009 - 2026)
Portland General Electric (POR) posted Weighted Average Shares Outstanding of 115.73 million for Q3 2026, up 5.0% from 110.17 million a year earlier and unchanged from the prior quarter.
Portland General Electric (POR) Weighted Average Shares Outstanding (2009 - 2026) Analysis & Trends
For FY2025, Portland General Electric's Weighted Average Shares Outstanding came in at 110.47 million, up 6.3% from FY2024.
- Annual Weighted Average Shares Outstanding has increased for three consecutive years, with a five-year compound annual growth rate of 4.3% (FY2020 to FY2025).
- In prior years, Portland General Electric's Weighted Average Shares Outstanding was 103.95 million in FY2024 (+6.3%), 97.76 million in FY2023 (+9.5%), 89.29 million in FY2022 (-0.2%) and 89.48 million in FY2021 (unchanged).
- On a year-over-year basis, Weighted Average Shares Outstanding has increased in each of the last 15 quarters, with growth averaging 6.2% over the last eight quarters.
- The strongest year-over-year quarter for Weighted Average Shares Outstanding in the past five years was Q3 2023, with growth of 13.0%; the weakest was Q2 2022, with a decline of 0.4%.
- According to Business Quant data, Weighted Average Shares Outstanding for the three prior quarters was 115.73 million (Q2 2026), 115.64 million (Q1 2026) and 110.47 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Wisconsin Electric Power | 99,216.00 Bn | 99,215.99 Bn | 911.30 Mn |
| 2 | Enel Chile | 301.57 Bn | 301.57 Bn | 1.33 Bn |
| 3 | Nextera Energy | 180.93 Bn | 179.04 Bn | - |
| 4 | Southern | 109.04 Bn | 101.70 Bn | 7.31 Bn |
| 5 | Duke Energy | 100.59 Bn | 99.24 Bn | 6.37 Bn |
| 6 | National Grid | 86.94 Bn | 59.27 Bn | - |
| 7 | American Electric Power | 69.61 Bn | 68.67 Bn | 4.75 Bn |
| 8 | Entergy | 53.37 Bn | 42.94 Bn | - |
| 9 | Sempra | 51.29 Bn | 84.11 Bn | - |
| 10 | Portland General Electric | 5.46 Bn | 4.97 Bn | - |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 118.20 Mn |
| Jun 30, 2026 | 115.73 Mn |
| Mar 31, 2026 | 115.64 Mn |
| Dec 31, 2025 | 110.47 Mn |
| Sep 30, 2025 | 110.17 Mn |
| Jun 30, 2025 | 109.52 Mn |
| Mar 31, 2025 | 109.42 Mn |
| Dec 31, 2024 | 103.95 Mn |
| Sep 30, 2024 | 103.85 Mn |
| Jun 30, 2024 | 103.03 Mn |
| Mar 31, 2024 | 101.30 Mn |
| Dec 31, 2023 | 97.76 Mn |
| Sep 30, 2023 | 100.85 Mn |
| Jun 30, 2023 | 97.09 Mn |
| Mar 31, 2023 | 91.84 Mn |
| Dec 31, 2022 | 89.29 Mn |
| Sep 30, 2022 | 89.26 Mn |
| Jun 30, 2022 | 89.23 Mn |
| Mar 31, 2022 | 89.40 Mn |
| Dec 31, 2021 | 89.48 Mn |
Portland General Electric Weighted Average 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=weighted-average-shares-outstanding&ticker=POR&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "weighted-average-shares-outstanding", "ticker": "POR", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=weighted-average-shares-outstanding&ticker=POR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();