Vishay Precision (VPG) Operating Expenses (2010 - 2026)
Vishay Precision's Operating Expenses came in at $32.76 million for Q2 2026, up 17.4% from $27.9 million a year earlier and up 0.7% from the prior quarter.
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Analysis
Vishay Precision (VPG) Operating Expenses (2010 - 2026) Analysis & Trends
Over the trailing twelve months to Jul 4, 2026, Vishay Precision reported Operating Expenses of $121.43 million, up 11.5% year-over-year; for FY2025, it was $111.14 million, up 2.3% from FY2024.
- Operating Expenses has increased in each of the last five years, with a five-year compound annual growth rate of 7.3% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $108.61 million in FY2024 (+0.2%), $108.43 million in FY2023 (+2.5%), $105.8 million in FY2022 (+9.7%) and $96.47 million in FY2021 (+23.3%).
- The Q2 2026 figure represents the highest quarterly Operating Expenses in data going back to Q2 2010.
- Year-over-year, Operating Expenses has increased for five consecutive quarters, with growth averaging 5.7% over the last eight quarters.
- The fastest year-over-year change in Operating Expenses over five years came in Q4 2021 (growth of 33.8%), and the weakest in Q3 2024 (a decline of 4.8%).
- Business Quant data shows VPG's Operating Expenses at $32.53 million (Q1 2026), $28.63 million (Q4 2025) and $27.51 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Caterpillar | 372.79 Bn | 344.49 Bn | 7.76 Bn | 16.25 Bn |
| 2 | Amphenol | 207.98 Bn | 202.68 Bn | 3.55 Bn | 963.40 Mn |
| 3 | Deere | 181.02 Bn | 189.78 Bn | 4.66 Bn | 10.73 Bn |
| 4 | Eaton | 166.86 Bn | 164.09 Bn | 2.86 Bn | 1.46 Bn |
| 5 | Parker-Hannifin | 120.45 Bn | 118.58 Bn | 2.25 Bn | 874.00 Mn |
| 6 | Vertiv Holdings | 92.94 Bn | 83.56 Bn | 1.23 Bn | 490.50 Mn |
| 7 | Emerson Electric | 86.56 Bn | 79.32 Bn | 2.66 Bn | 1.34 Bn |
| 8 | 3M | 84.72 Bn | 66.18 Bn | 2.68 Bn | 5.52 Bn |
| 9 | Illinois Tool Works | 73.32 Bn | 69.88 Bn | 1.90 Bn | - |
| 10 | Vishay Precision | 1.86 Bn | 1.53 Bn | 32.44 Mn | 32.76 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 4, 2026 | 32.76 Mn |
| Apr 4, 2026 | 32.53 Mn |
| Dec 31, 2025 | 28.63 Mn |
| Sep 27, 2025 | 27.51 Mn |
| Jun 28, 2025 | 27.90 Mn |
| Mar 29, 2025 | 27.11 Mn |
| Dec 31, 2024 | 27.47 Mn |
| Sep 28, 2024 | 26.44 Mn |
| Jun 29, 2024 | 26.50 Mn |
| Mar 30, 2024 | 28.19 Mn |
| Dec 31, 2023 | 26.53 Mn |
| Sep 30, 2023 | 27.76 Mn |
| Jul 1, 2023 | 26.96 Mn |
| Apr 1, 2023 | 27.28 Mn |
| Dec 31, 2022 | 26.65 Mn |
| Oct 1, 2022 | 25.47 Mn |
| Jul 2, 2022 | 26.78 Mn |
| Apr 2, 2022 | 26.97 Mn |
| Dec 31, 2021 | 26.06 Mn |
| Oct 2, 2021 | 24.58 Mn |
API Access
Vishay Precision 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=VPG&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "VPG", "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=VPG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();