Techprecision (TPCS) Total Liabilities (2011 - 2026)
Techprecision's Total Liabilities came in at $23.63 million for fiscal Q1 2027 (quarter ended Jun 30, 2026), down 1.3% from $23.93 million a year earlier and down 4.0% from the prior quarter.
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Analysis
Techprecision (TPCS) Total Liabilities (2011 - 2026) Analysis & Trends
At the end of FY2026 (ended Mar 31, 2026), Techprecision's Total Liabilities was $24.6 million, down 0.8% from FY2025.
- Total Liabilities carries a five-year compound annual growth rate of 32.3% (FY2021 to FY2026).
- Going back by fiscal year, Total Liabilities was $24.79 million in FY2025 (-8.0%), $26.94 million in FY2024 (+24.7%), $21.61 million in FY2023 (-4.3%) and $22.59 million in FY2022 (+272.6%).
- The fiscal Q1 2027 figure represents the lowest quarterly Total Liabilities since fiscal Q3 2024.
- Year-over-year, Total Liabilities increased in three of the last eight quarters, with an average decline of 1.2%.
- The fastest year-over-year change in Total Liabilities over five years came in fiscal Q1 2023 (growth of 451.0%), and the weakest in fiscal Q1 2026 (a decline of 14.1%).
- Business Quant data shows TPCS's Total Liabilities at $24.6 million (Q4 2026), $24.82 million (Q3 2026) and $24.74 million (Q2 2026) in the three fiscal quarters before Q1 2027.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Caterpillar | 376.87 Bn | 348.57 Bn | 7.76 Bn | 83.22 Bn |
| 2 | Amphenol | 208.65 Bn | 203.35 Bn | 3.55 Bn | 29.19 Bn |
| 3 | Deere | 185.97 Bn | 194.73 Bn | 4.66 Bn | 79.61 Bn |
| 4 | Eaton | 167.50 Bn | 164.73 Bn | 2.86 Bn | 35.88 Bn |
| 5 | Parker-Hannifin | 122.25 Bn | 120.39 Bn | 2.25 Bn | 15.46 Bn |
| 6 | Vertiv Holdings | 93.95 Bn | 84.57 Bn | 1.23 Bn | 11.14 Bn |
| 7 | Emerson Electric | 88.90 Bn | 81.65 Bn | 2.66 Bn | 21.81 Bn |
| 8 | 3M | 87.39 Bn | 68.85 Bn | 2.68 Bn | 31.92 Bn |
| 9 | Illinois Tool Works | 78.00 Bn | 74.56 Bn | 1.90 Bn | 13.60 Bn |
| 10 | Techprecision | 52.72 Mn | 51.74 Mn | 1.40 Mn | 23.63 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 23.63 Mn |
| Mar 31, 2026 | 24.60 Mn |
| Dec 31, 2025 | 24.82 Mn |
| Sep 30, 2025 | 24.74 Mn |
| Jun 30, 2025 | 23.93 Mn |
| Mar 31, 2025 | 24.79 Mn |
| Dec 31, 2024 | 24.06 Mn |
| Sep 30, 2024 | 26.13 Mn |
| Jun 30, 2024 | 27.85 Mn |
| Mar 31, 2024 | 26.94 Mn |
| Dec 31, 2023 | 21.91 Mn |
| Sep 30, 2023 | 24.46 Mn |
| Jun 30, 2023 | 23.67 Mn |
| Mar 31, 2023 | 21.61 Mn |
| Dec 31, 2022 | 21.81 Mn |
| Sep 30, 2022 | 21.35 Mn |
| Jun 30, 2022 | 22.83 Mn |
| Mar 31, 2022 | 22.59 Mn |
| Dec 31, 2021 | 21.56 Mn |
| Sep 30, 2021 | 20.03 Mn |
API Access
Techprecision 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=TPCS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "TPCS", "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=TPCS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();