Techprecision (TPCS) Operating Expenses (2010 - 2026)
Techprecision (TPCS) recorded Operating Expenses of $1.45 million in fiscal Q1 2027 (quarter ended Jun 30, 2026), down 3.2% from $1.49 million a year earlier but up 11.2% from the prior quarter.
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Analysis
Techprecision (TPCS) Operating Expenses (2010 - 2026) Analysis & Trends
On a TTM basis, Techprecision's Operating Expenses came in at $5.99 million as of Jun 30, 2026, down 6.3% year-over-year; for FY2026 (ended Mar 31, 2026), it was $6.04 million, down 6.9% from FY2025.
- Annual Operating Expenses has a five-year compound annual growth rate of 16.3% (FY2021 to FY2026).
- Across earlier fiscal years, Operating Expenses came in at $6.49 million in FY2025 (-38.2%), $10.5 million in FY2024 (+38.7%), $7.57 million in FY2023 (+53.2%) and $4.94 million in FY2022 (+73.8%).
- Quarterly Operating Expenses has ranged from $1.17 million in fiscal Q2 2022 to $3.69 million in fiscal Q4 2024 over the past five years.
- On a year-over-year basis, Operating Expenses rose in two of the last eight quarters, with an average decline of 14.1%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 133.1% in fiscal Q4 2024, against a decline of 53.4% in fiscal Q4 2025 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $1.3 million (Q4 2026), $1.73 million (Q3 2026) and $1.52 million (Q2 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Caterpillar | 376.87 Bn | 348.57 Bn | 7.76 Bn | 16.25 Bn |
| 2 | Amphenol | 208.65 Bn | 203.35 Bn | 3.55 Bn | 963.40 Mn |
| 3 | Deere | 185.97 Bn | 194.73 Bn | 4.66 Bn | 10.73 Bn |
| 4 | Eaton | 167.50 Bn | 164.73 Bn | 2.86 Bn | 1.46 Bn |
| 5 | Parker-Hannifin | 122.25 Bn | 120.39 Bn | 2.25 Bn | 874.00 Mn |
| 6 | Vertiv Holdings | 93.95 Bn | 84.57 Bn | 1.23 Bn | 490.50 Mn |
| 7 | Emerson Electric | 88.90 Bn | 81.65 Bn | 2.66 Bn | 1.34 Bn |
| 8 | 3M | 87.39 Bn | 68.85 Bn | 2.68 Bn | 5.52 Bn |
| 9 | Illinois Tool Works | 78.00 Bn | 74.56 Bn | 1.90 Bn | - |
| 10 | Techprecision | 52.72 Mn | 51.74 Mn | 1.40 Mn | 1.45 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.45 Mn |
| Mar 31, 2026 | 1.30 Mn |
| Dec 31, 2025 | 1.73 Mn |
| Sep 30, 2025 | 1.52 Mn |
| Jun 30, 2025 | 1.49 Mn |
| Mar 31, 2025 | 1.72 Mn |
| Dec 31, 2024 | 1.69 Mn |
| Sep 30, 2024 | 1.50 Mn |
| Jun 30, 2024 | 1.58 Mn |
| Mar 31, 2024 | 3.69 Mn |
| Dec 31, 2023 | 2.16 Mn |
| Sep 30, 2023 | 1.63 Mn |
| Jun 30, 2023 | 1.27 Mn |
| Mar 31, 2023 | 1.58 Mn |
| Dec 31, 2022 | 1.22 Mn |
| Sep 30, 2022 | 1.83 Mn |
| Jun 30, 2022 | 1.38 Mn |
| Mar 31, 2022 | 1.41 Mn |
| Dec 31, 2021 | 1.62 Mn |
| Sep 30, 2021 | 1.17 Mn |
API Access
Techprecision Operating Expenses 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=operating-expenses&ticker=TPCS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "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=operating-expenses&ticker=TPCS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();