Realloys (ALOY) Shares Outstanding (Diluted) (2013 - 2026)
Realloys' Weighted Average Shares Outstanding (Diluted) came in at 62.14 million for Q2 2026, up 50.5% from 41.29 million a year earlier and up 15.2% from the prior quarter.
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Analysis
Realloys (ALOY) Shares Outstanding (Diluted) (2013 - 2026) Analysis & Trends
For FY2025, Realloys' Weighted Average Shares Outstanding (Diluted) was 41.29 million, up 213.1% from FY2024.
- Weighted Average Shares Outstanding (Diluted) carries a five-year compound annual growth rate of 25.8% (FY2020 to FY2025).
- Going back by year, Weighted Average Shares Outstanding (Diluted) was 13.19 million in FY2024 (unchanged), 13.19 million in FY2023 (unchanged), 13.19 million in FY2022 (+35.7%) and 9.72 million in FY2021 (-25.7%).
- The Q2 2026 figure represents the highest quarterly Weighted Average Shares Outstanding (Diluted) in data going back to Q1 2020.
- Year-over-year, Weighted Average Shares Outstanding (Diluted) has increased for six consecutive quarters, with growth averaging 112.8% over the last eight quarters.
- The fastest year-over-year change in Weighted Average Shares Outstanding (Diluted) over five years came in Q4 2025 (growth of 213.1%), and the weakest in Q3 2021 (a decline of 25.7%).
- Business Quant data shows ALOY's Weighted Average Shares Outstanding (Diluted) at 53.95 million (Q1 2026), 41.29 million (Q4 2025) and 41.29 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Shares Outstanding (Dil.) (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 406.71 Bn | 371.66 Bn | 1.93 Bn | 2.57 Bn |
| 2 | Oracle | 356.71 Bn | 229.27 Bn | 18.57 Bn | 3.00 Bn |
| 3 | Sap Se | 287.26 Bn | 215.24 Bn | 8.64 Bn | 1.18 Bn |
| 4 | Salesforce | 175.69 Bn | 131.56 Bn | 8.70 Bn | 821.00 Mn |
| 5 | Automatic Data Processing | 120.83 Bn | 107.63 Bn | 2.53 Bn | 397.60 Mn |
| 6 | ServiceNow | 103.38 Bn | 82.65 Bn | 2.90 Bn | 1.04 Bn |
| 7 | Intuit | 91.37 Bn | 70.72 Bn | 3.44 Bn | 277.00 Mn |
| 8 | Relx | 72.62 Bn | 72.62 Bn | - | 1.84 Bn |
| 9 | Strategy | 48.71 Bn | 35.85 Bn | 89.63 Mn | 428.05 Mn |
| 10 | Realloys | 427.14 Mn | 262.10 Mn | 475,000.00 | 62.14 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 62.14 Mn |
| Mar 31, 2026 | 53.95 Mn |
| Dec 31, 2025 | 41.29 Mn |
| Sep 30, 2025 | 41.29 Mn |
| Jun 30, 2025 | 41.29 Mn |
| Mar 31, 2025 | 32.59 Mn |
| Dec 31, 2024 | 13.19 Mn |
| Sep 30, 2024 | 13.19 Mn |
| Jun 30, 2024 | 13.19 Mn |
| Mar 31, 2024 | 13.19 Mn |
| Dec 31, 2023 | 13.19 Mn |
| Sep 30, 2023 | 13.19 Mn |
| Jun 30, 2023 | 13.19 Mn |
| Mar 31, 2023 | 13.19 Mn |
| Dec 31, 2022 | 13.19 Mn |
| Sep 30, 2022 | 13.19 Mn |
| Jun 30, 2022 | 13.19 Mn |
| Mar 31, 2022 | 13.18 Mn |
| Dec 31, 2021 | 9.72 Mn |
| Sep 30, 2021 | 9.72 Mn |
API Access
Realloys 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=ALOY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "shares-outstanding-diluted", "ticker": "ALOY", "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=ALOY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();