Tetra Technologies (TTI) Total Liabilities (2009 - 2026)
Tetra Technologies' Total Liabilities came in at $392.32 million for Q2 2026, up 10.2% from $355.96 million a year earlier and up 4.1% from the prior quarter.
Tetra Technologies (TTI) Total Liabilities (2009 - 2026) Analysis & Trends
At the end of FY2025, Tetra Technologies' Total Liabilities was $392.01 million, up 11.4% from FY2024.
- Total Liabilities has increased in each of the last four years, though with a five-year compound annual growth rate of -18.1% (FY2020 to FY2025).
- Going back by year, Total Liabilities was $351.89 million in FY2024 (+6.1%), $331.63 million in FY2023 (+1.1%), $327.97 million in FY2022 (+9.4%) and $299.7 million in FY2021 (-71.8%).
- The Q2 2026 figure represents the highest quarterly Total Liabilities since Q2 2024.
- Year-over-year, Total Liabilities has increased for four consecutive quarters, with an average decline of 0.1% over the last eight quarters.
- The fastest year-over-year change in Total Liabilities over five years came in Q1 2024 (growth of 43.7%), and the weakest in Q4 2021 (a decline of 71.8%).
- Business Quant data shows TTI's Total Liabilities at $376.73 million (Q1 2026), $392.01 million (Q4 2025) and $358.49 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Slb | 76.39 Bn | 73.50 Bn | 1.40 Bn | 28.28 Bn |
| 2 | Baker Hughes | 56.70 Bn | 19.98 Bn | 1.58 Bn | 32.54 Bn |
| 3 | TechnipFMC | 27.74 Bn | 23.88 Bn | 684.70 Mn | 7.09 Bn |
| 4 | Halliburton | 27.03 Bn | 18.79 Bn | 804.00 Mn | 14.78 Bn |
| 5 | Nov | 6.97 Bn | 1.76 Bn | 521.00 Mn | 4.94 Bn |
| 6 | Noble | 6.81 Bn | 4.74 Bn | 239.27 Mn | 2.76 Bn |
| 7 | Weatherford International | 5.95 Bn | 1.88 Bn | 333.00 Mn | 3.31 Bn |
| 8 | Transocean | 5.90 Bn | 3.61 Bn | 358.00 Mn | 6.80 Bn |
| 9 | Valaris | 5.52 Bn | 3.13 Bn | 123.70 Mn | 2.23 Bn |
| 10 | Tetra Technologies | 875.11 Mn | 533.60 Mn | 45.71 Mn | 392.32 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 392.32 Mn |
| Mar 31, 2026 | 376.73 Mn |
| Dec 31, 2025 | 392.01 Mn |
| Sep 30, 2025 | 358.49 Mn |
| Jun 30, 2025 | 355.96 Mn |
| Mar 31, 2025 | 342.34 Mn |
| Dec 31, 2024 | 351.89 Mn |
| Sep 30, 2024 | 345.75 Mn |
| Jun 30, 2024 | 451.62 Mn |
| Mar 31, 2024 | 459.05 Mn |
| Dec 31, 2023 | 331.63 Mn |
| Sep 30, 2023 | 331.28 Mn |
| Jun 30, 2023 | 332.94 Mn |
| Mar 31, 2023 | 319.43 Mn |
| Dec 31, 2022 | 327.97 Mn |
| Sep 30, 2022 | 311.73 Mn |
| Jun 30, 2022 | 311.08 Mn |
| Mar 31, 2022 | 299.87 Mn |
| Dec 31, 2021 | 299.70 Mn |
| Sep 30, 2021 | 311.16 Mn |
Tetra Technologies Total Liabilities 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=total-liabilities&ticker=TTI&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "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=total-liabilities&ticker=TTI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();