Prologis (PLD) Weighted Average Shares Outstanding (2009 - 2026)
Prologis' Weighted Average Shares Outstanding came in at 944.13 million for Q3 2026, up 1.6% from 928.85 million a year earlier and up 1.2% from the prior quarter.
Prologis (PLD) Weighted Average Shares Outstanding (2009 - 2026) Analysis & Trends
For FY2025, Prologis' Weighted Average Shares Outstanding was 928.47 million, up 0.2% from FY2024.
- Weighted Average Shares Outstanding has increased in each of the last 16 years, with a five-year compound annual growth rate of 5.0% (FY2020 to FY2025).
- Going back by year, Weighted Average Shares Outstanding was 926.17 million in FY2024 (+0.2%), 924.35 million in FY2023 (+17.7%), 785.68 million in FY2022 (+6.3%) and 739.36 million in FY2021 (+1.5%).
- The Q3 2026 figure represents the highest quarterly Weighted Average Shares Outstanding in data going back to Q2 2009.
- Year-over-year, Weighted Average Shares Outstanding has increased for 58 consecutive quarters, with growth averaging 0.5% over the last eight quarters.
- The year-over-year growth in Weighted Average Shares Outstanding has ranged between 0.2% (Q1 2024) and 24.8% (Q3 2023) over the last five years.
- Business Quant data shows PLD's Weighted Average Shares Outstanding at 933.09 million (Q2 2026), 931.26 million (Q1 2026) and 928.47 million (Q4 2025) in the three quarters before Q3 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Welltower | 181.70 Bn | 168.77 Bn | 1.47 Bn |
| 2 | Prologis | 123.65 Bn | 122.03 Bn | - |
| 3 | Simon Property | 80.48 Bn | 78.58 Bn | - |
| 4 | Public Storage | 62.76 Bn | 62.20 Bn | 112.08 Mn |
| 5 | Realty Income | 56.61 Bn | 57.99 Bn | - |
| 6 | Ryman Hospitality Properties | 47.80 Bn | 46.64 Bn | 266.41 Mn |
| 7 | Ventas | 47.78 Bn | 46.95 Bn | -3.39 Bn |
| 8 | Vivmark Residential | 38.23 Bn | 37.98 Bn | - |
| 9 | Extra Space Storage | 33.20 Bn | 32.98 Bn | 650.96 Mn |
| 10 | Vici Properties | 27.53 Bn | 26.31 Bn | 1.06 Bn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 944.13 Mn |
| Jun 30, 2026 | 933.09 Mn |
| Mar 31, 2026 | 952.98 Mn |
| Dec 31, 2025 | 928.47 Mn |
| Sep 30, 2025 | 928.85 Mn |
| Jun 30, 2025 | 928.48 Mn |
| Mar 31, 2025 | 927.34 Mn |
| Dec 31, 2024 | 926.17 Mn |
| Sep 30, 2024 | 926.43 Mn |
| Jun 30, 2024 | 926.28 Mn |
| Mar 31, 2024 | 925.32 Mn |
| Dec 31, 2023 | 924.35 Mn |
| Sep 30, 2023 | 924.40 Mn |
| Jun 30, 2023 | 924.19 Mn |
| Mar 31, 2023 | 923.89 Mn |
| Dec 31, 2022 | 785.68 Mn |
| Sep 30, 2022 | 740.72 Mn |
| Jun 30, 2022 | 740.64 Mn |
| Mar 31, 2022 | 740.37 Mn |
| Dec 31, 2021 | 739.36 Mn |
Prologis 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=PLD&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "weighted-average-shares-outstanding", "ticker": "PLD", "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=PLD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();