Lincoln Electric Holdings (LECO) Operating Expenses (2009 - 2026)
Lincoln Electric Holdings' Operating Expenses was $228.35 million in Q2 2026, up 7.0% from $213.4 million a year earlier and up 7.2% from the prior quarter.
Lincoln Electric Holdings (LECO) Operating Expenses (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Lincoln Electric Holdings' Operating Expenses was $843.59 million through Jun 30, 2026, up 3.9% year-over-year; for FY2025, it was $816.19 million, down 2.4% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 6.7% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $836.45 million in FY2024 (+11.9%), $747.6 million in FY2023 (+11.8%), $668.42 million in FY2022 (+10.1%) and $606.94 million in FY2021 (+3.0%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses since Q2 2024.
- Compared with a year earlier, Operating Expenses was higher in five of the last eight quarters, with growth averaging 3.2%.
- The best year-over-year quarter for Operating Expenses over five years was Q2 2024 (growth of 20.2%); the worst was Q2 2025 (a decline of 9.2%).
- Per Business Quant data, LECO's Operating Expenses in the three quarters before Q2 2026 was $212.97 million (Q1 2026), $189.61 million (Q4 2025) and $212.65 million (Q3 2025).
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 | Lincoln Electric Holdings | 14.42 Bn | 13.28 Bn | 449.00 Mn | 228.35 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 228.35 Mn |
| Mar 31, 2026 | 212.97 Mn |
| Dec 31, 2025 | 189.61 Mn |
| Sep 30, 2025 | 212.65 Mn |
| Jun 30, 2025 | 213.40 Mn |
| Mar 31, 2025 | 200.53 Mn |
| Dec 31, 2024 | 191.61 Mn |
| Sep 30, 2024 | 206.52 Mn |
| Jun 30, 2024 | 234.98 Mn |
| Mar 31, 2024 | 203.35 Mn |
| Dec 31, 2023 | 167.00 Mn |
| Sep 30, 2023 | 194.19 Mn |
| Jun 30, 2023 | 195.42 Mn |
| Mar 31, 2023 | 190.99 Mn |
| Dec 31, 2022 | 166.50 Mn |
| Sep 30, 2022 | 167.41 Mn |
| Jun 30, 2022 | 165.95 Mn |
| Mar 31, 2022 | 168.57 Mn |
| Dec 31, 2021 | 152.31 Mn |
| Sep 30, 2021 | 152.60 Mn |
Lincoln Electric Holdings 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=LECO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "LECO", "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=LECO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();