Donnelley Financial Solutions (DFIN) Shares Outstanding (Entity) (2015 - 2026)
Donnelley Financial Solutions (DFIN) reported Shares Outstanding (Entity) of 24.7 million for Q2 2026, down 10.2% from 27.5 million a year earlier and down 2.8% from the prior quarter.
Donnelley Financial Solutions (DFIN) Shares Outstanding (Entity) (2015 - 2026) Analysis & Trends
For FY2025, Donnelley Financial Solutions posted Shares Outstanding (Entity) of 25.6 million, down 10.8% from FY2024.
- Shares Outstanding (Entity) has a five-year compound annual growth rate of -5.1% (FY2020 to FY2025).
- By year, Shares Outstanding (Entity) came in at 28.7 million in FY2024 (-1.4%), 29.1 million in FY2023 (+0.7%), 28.9 million in FY2022 (-12.4%) and 33 million in FY2021 (-0.9%).
- The Q2 2026 figure ranks as the lowest quarterly Shares Outstanding (Entity) in data going back to Q3 2015.
- Year over year, Shares Outstanding (Entity) has now declined in each of the last ten quarters, with an average decline of 6.2% over the last eight quarters.
- The high point for year-over-year Shares Outstanding (Entity) in five years was Q4 2023 (growth of 0.7%); the low point was Q4 2022 (a decline of 12.4%).
- Per Business Quant data, the three quarters before Q2 2026 came in at 25.4 million (Q1 2026), 25.6 million (Q4 2025) and 26.9 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Shares Outstanding (Entity.) (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 449.46 Bn | 418.52 Bn | 1.64 Bn | 2.40 Bn |
| 2 | Oracle | 415.29 Bn | 287.84 Bn | - | 3.02 Bn |
| 3 | Sap Se | 256.30 Bn | 177.39 Bn | 8.40 Bn | - |
| 4 | Salesforce | 188.94 Bn | 144.82 Bn | 8.70 Bn | 823.00 Mn |
| 5 | ServiceNow | 138.57 Bn | 117.03 Bn | 2.82 Bn | 1.03 Bn |
| 6 | Automatic Data Processing | 102.66 Bn | 84.78 Bn | 2.51 Bn | 397.80 Mn |
| 7 | Intuit | 74.00 Bn | 53.35 Bn | 3.44 Bn | 268.38 Mn |
| 8 | Relx | 60.34 Bn | 57.31 Bn | - | - |
| 9 | Strategy | 53.88 Bn | 46.87 Bn | 81.55 Mn | 351.96 Mn |
| 10 | Donnelley Financial Solutions | 1.16 Bn | 1.07 Bn | 148.00 Mn | 24.70 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 24.70 Mn |
| Mar 31, 2026 | 25.40 Mn |
| Dec 31, 2025 | 25.60 Mn |
| Sep 30, 2025 | 26.90 Mn |
| Jun 30, 2025 | 27.50 Mn |
| Mar 31, 2025 | 28.20 Mn |
| Dec 31, 2024 | 28.70 Mn |
| Sep 30, 2024 | 28.90 Mn |
| Jun 30, 2024 | 29.10 Mn |
| Mar 31, 2024 | 29.40 Mn |
| Dec 31, 2023 | 29.10 Mn |
| Sep 30, 2023 | 29.10 Mn |
| Jun 30, 2023 | 29.40 Mn |
| Mar 31, 2023 | 29.50 Mn |
| Dec 31, 2022 | 28.90 Mn |
| Sep 30, 2022 | 29.30 Mn |
| Jun 30, 2022 | 30.30 Mn |
| Mar 31, 2022 | 32.40 Mn |
| Dec 31, 2021 | 33.00 Mn |
| Sep 30, 2021 | 33.40 Mn |
Donnelley Financial Solutions Shares Outstanding (Entity) 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-entity&ticker=DFIN&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "shares-outstanding-entity", "ticker": "DFIN", "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-entity&ticker=DFIN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();