Harrow (HROW) Shares Outstanding (Diluted) (2016 - 2026)
Harrow (HROW) recorded Shares Outstanding (Diluted) of 37.35 million in Q2 2026, down 3.9% from 38.85 million a year earlier but up 0.3% from the prior quarter.
Harrow (HROW) Shares Outstanding (Diluted) (2016 - 2026) Analysis & Trends
For FY2025, Harrow reported Shares Outstanding (Diluted) of 36.76 million, up 3.1% from FY2024.
- Annual Shares Outstanding (Diluted) has increased for five straight years, with a five-year compound annual growth rate of 7.3% (FY2020 to FY2025).
- Across earlier years, Shares Outstanding (Diluted) came in at 35.65 million in FY2024 (+9.3%), 32.62 million in FY2023 (+18.8%), 27.46 million in FY2022 (+1.3%) and 27.11 million in FY2021 (+4.7%).
- Quarterly Shares Outstanding (Diluted) has ranged from 27.11 million in Q3 2021 to 38.88 million in Q3 2025 over the past five years.
- On a year-over-year basis, Shares Outstanding (Diluted) rose in seven of the last eight quarters, with growth averaging 4.5%.
- Peak year-over-year performance for Shares Outstanding (Diluted) in the last five years was growth of 25.2% in Q3 2023, against a decline of 3.9% in Q2 2026 at the low end.
- Per Business Quant, the preceding three quarters came in at 37.23 million (Q1 2026), 36.76 million (Q4 2025) and 38.88 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Shares Outstanding (Dil.) (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,261.99 Bn | 1,235.61 Bn | 20.46 Bn | 893.40 Mn |
| 2 | Johnson & Johnson | 678.93 Bn | 598.79 Bn | 17.30 Bn | 2.45 Bn |
| 3 | AbbVie | 518.29 Bn | 486.30 Bn | 13.12 Bn | 1.77 Bn |
| 4 | Merck | 365.98 Bn | 328.92 Bn | 13.19 Bn | 2.48 Bn |
| 5 | Novartis Ag | 316.85 Bn | 290.09 Bn | - | 1.96 Bn |
| 6 | Astrazeneca | 293.40 Bn | 267.29 Bn | 13.26 Bn | 1.56 Bn |
| 7 | Amgen | 251.78 Bn | 203.43 Bn | 7.58 Bn | 546.00 Mn |
| 8 | Gilead Sciences | 210.61 Bn | 185.71 Bn | 6.73 Bn | 1.25 Bn |
| 9 | Pfizer | 166.87 Bn | 114.23 Bn | 12.56 Bn | 5.75 Bn |
| 10 | Harrow | 1.03 Bn | 708.48 Mn | 50.36 Mn | 37.35 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 37.35 Mn |
| Mar 31, 2026 | 37.23 Mn |
| Dec 31, 2025 | 36.76 Mn |
| Sep 30, 2025 | 38.88 Mn |
| Jun 30, 2025 | 38.85 Mn |
| Mar 31, 2025 | 35.83 Mn |
| Dec 31, 2024 | 35.65 Mn |
| Sep 30, 2024 | 35.70 Mn |
| Jun 30, 2024 | 35.62 Mn |
| Mar 31, 2024 | 35.47 Mn |
| Dec 31, 2023 | 32.62 Mn |
| Sep 30, 2023 | 34.26 Mn |
| Jun 30, 2023 | 30.46 Mn |
| Mar 31, 2023 | 30.29 Mn |
| Dec 31, 2022 | 27.46 Mn |
| Sep 30, 2022 | 27.35 Mn |
| Jun 30, 2022 | 27.30 Mn |
| Mar 31, 2022 | 27.23 Mn |
| Dec 31, 2021 | 27.11 Mn |
| Sep 30, 2021 | 27.11 Mn |
Harrow 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=HROW&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "shares-outstanding-diluted", "ticker": "HROW", "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=HROW&period=max&api_key=YOUR_API_KEY");
const data = await res.json();