Diebold Nixdorf (DBD) Shares Outstanding (Diluted) (2009 - 2026)
Diebold Nixdorf (DBD) reported Shares Outstanding (Diluted) of 35.3 million for Q2 2026, down 5.9% from 37.5 million a year earlier and down 1.1% from the prior quarter.
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Analysis
Diebold Nixdorf (DBD) Shares Outstanding (Diluted) (2009 - 2026) Analysis & Trends
For FY2025, Diebold Nixdorf posted Shares Outstanding (Diluted) of 37.2 million, down 1.1% from FY2024.
- Shares Outstanding (Diluted) has a five-year compound annual growth rate of -13.7% (FY2020 to FY2025).
- By year, Shares Outstanding (Diluted) came in at 37.6 million in FY2024 (unchanged), 37.6 million in FY2023 (-52.4%), 79 million in FY2022 (+0.9%) and 78.3 million in FY2021 (+0.9%).
- The Q2 2026 figure ranks as the lowest quarterly Shares Outstanding (Diluted) in data going back to Q2 2009.
- Year over year, Shares Outstanding (Diluted) has now declined in each of the last five quarters, with an average decline of 2.0% over the last seven quarters.
- The high point for year-over-year Shares Outstanding (Diluted) in five years was Q3 2022 (growth of 1.9%); the low point was Q4 2023 (a decline of 52.4%).
- Per Business Quant data, the three quarters before Q2 2026 came in at 35.7 million (Q1 2026), 37.2 million (Q4 2025) and 37 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Shares Outstanding (Dil.) (Qtr) |
|---|---|---|---|---|---|
| 1 | Bryn | 945.00 Bn | 945.00 Bn | - | - |
| 2 | Veeva Systems | 46.20 Bn | 18.45 Bn | 695.95 Mn | 165.06 Mn |
| 3 | Samsara | 22.32 Bn | 19.09 Bn | 392.58 Mn | 590.46 Mn |
| 4 | Toast | 16.73 Bn | 9.40 Bn | 516.00 Mn | 590.00 Mn |
| 5 | Ptc | 15.53 Bn | 14.35 Bn | 490.47 Mn | 114.98 Mn |
| 6 | Duolingo | 13.32 Bn | 8.49 Bn | 216.74 Mn | 50.03 Mn |
| 7 | Trimble | 13.32 Bn | 12.38 Bn | 674.90 Mn | 233.00 Mn |
| 8 | Manhattan Associates | 11.58 Bn | 10.58 Bn | 168.33 Mn | 59.00 Mn |
| 9 | Costar | 11.10 Bn | 5.07 Bn | 728.00 Mn | 404.40 Mn |
| 10 | Diebold Nixdorf | 2.08 Bn | 752.15 Mn | 239.60 Mn | 35.30 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 35.30 Mn |
| Mar 31, 2026 | 35.70 Mn |
| Dec 31, 2025 | 37.20 Mn |
| Sep 30, 2025 | 37.00 Mn |
| Jun 30, 2025 | 37.50 Mn |
| Mar 31, 2025 | 37.60 Mn |
| Dec 31, 2024 | 37.60 Mn |
| Sep 30, 2024 | 37.60 Mn |
| Jun 30, 2024 | 37.70 Mn |
| Mar 31, 2024 | 37.60 Mn |
| Dec 31, 2023 | 37.60 Mn |
| Sep 30, 2023 | 37.60 Mn |
| Jun 30, 2023 | 80.00 Mn |
| Mar 31, 2023 | 79.30 Mn |
| Dec 31, 2022 | 79.00 Mn |
| Sep 30, 2022 | 79.10 Mn |
| Jun 30, 2022 | 78.30 Mn |
| Mar 31, 2022 | 78.30 Mn |
| Dec 31, 2021 | 78.30 Mn |
| Sep 30, 2021 | 77.60 Mn |
API Access
Diebold Nixdorf 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=DBD&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "shares-outstanding-diluted", "ticker": "DBD", "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=DBD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();