Tetra Technologies (TTI) Shares Outstanding (2009 - 2026)
Tetra Technologies (TTI) posted Weighted Average Shares Outstanding of 148.2 million for Q3 2026, up 11.1% from 133.42 million a year earlier and up 6.6% from the prior quarter.
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Analysis
Tetra Technologies (TTI) Shares Outstanding (2009 - 2026) Analysis & Trends
For FY2025, Tetra Technologies' Weighted Average Shares Outstanding came in at 133.2 million, up 1.5% from FY2024.
- Annual Weighted Average Shares Outstanding has increased for 16 consecutive years, with a five-year compound annual growth rate of 1.1% (FY2020 to FY2025).
- In prior years, Tetra Technologies' Weighted Average Shares Outstanding was 131.28 million in FY2024 (+1.3%), 129.57 million in FY2023 (+1.2%), 128.08 million in FY2022 (+1.2%) and 126.6 million in FY2021 (+0.6%).
- The Q3 2026 figure stands as the highest quarterly Weighted Average Shares Outstanding in data going back to Q2 2009.
- On a year-over-year basis, Weighted Average Shares Outstanding has increased in each of the last 26 quarters, with growth averaging 3.0% over the last eight quarters.
- Over the past five years, the year-over-year growth in Weighted Average Shares Outstanding ranged from 0.6% (Q4 2021) to 11.1% (Q3 2026).
- According to Business Quant data, Weighted Average Shares Outstanding for the three prior quarters was 139 million (Q2 2026), 134.5 million (Q1 2026) and 133.2 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Shares Outstanding (Qtr) |
|---|---|---|---|---|---|
| 1 | Slb | 73.81 Bn | 70.26 Bn | 1.57 Bn | 1.48 Bn |
| 2 | Baker Hughes | 47.88 Bn | 9.61 Bn | 1.96 Bn | 993.00 Mn |
| 3 | Halliburton | 26.33 Bn | 18.23 Bn | 840.00 Mn | 831.00 Mn |
| 4 | TechnipFMC | 25.25 Bn | 21.22 Bn | 728.70 Mn | 391.60 Mn |
| 5 | Noble | 6.55 Bn | 4.63 Bn | 228.22 Mn | 159.65 Mn |
| 6 | Nov | 6.31 Bn | 1.20 Bn | 439.00 Mn | 357.00 Mn |
| 7 | Weatherford International | 6.04 Bn | 1.78 Bn | 374.00 Mn | 71.90 Mn |
| 8 | Transocean | 5.85 Bn | 3.89 Bn | 348.00 Mn | 1.12 Bn |
| 9 | Valaris | 5.52 Bn | 3.27 Bn | 176.30 Mn | 69.40 Mn |
| 10 | Tetra Technologies | 893.65 Mn | 504.93 Mn | 35.10 Mn | 148.20 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 148.20 Mn |
| Jun 30, 2026 | 139.00 Mn |
| Mar 31, 2026 | 134.50 Mn |
| Dec 31, 2025 | 133.20 Mn |
| Sep 30, 2025 | 133.42 Mn |
| Jun 30, 2025 | 133.15 Mn |
| Mar 31, 2025 | 132.35 Mn |
| Dec 31, 2024 | 131.28 Mn |
| Sep 30, 2024 | 131.58 Mn |
| Jun 30, 2024 | 131.26 Mn |
| Mar 31, 2024 | 130.45 Mn |
| Dec 31, 2023 | 129.57 Mn |
| Sep 30, 2023 | 129.78 Mn |
| Jun 30, 2023 | 129.46 Mn |
| Mar 31, 2023 | 128.94 Mn |
| Dec 31, 2022 | 128.08 Mn |
| Sep 30, 2022 | 128.41 Mn |
| Jun 30, 2022 | 127.99 Mn |
| Mar 31, 2022 | 127.26 Mn |
| Dec 31, 2021 | 126.60 Mn |
API Access
Tetra Technologies 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=shares-outstanding&ticker=TTI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "shares-outstanding", "ticker": "TTI", "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&ticker=TTI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();