Weyco (WEYS) Property, Plant & Equipment (Net) (2010 - 2026)
Weyco (WEYS) posted Property, Plant & Equipment (Net) of $27.67 million for Q2 2026, down 0.4% from $27.78 million a year earlier but up 1.1% from the prior quarter.
Weyco (WEYS) Property, Plant & Equipment (Net) (2010 - 2026) Analysis & Trends
At the end of FY2025, Weyco's Property, Plant & Equipment (Net) came in at $27.41 million, down 2.7% from FY2024.
- Annual Property, Plant & Equipment (Net) shows a five-year compound annual growth rate of -2.3% (FY2020 to FY2025).
- In prior years, Weyco's Property, Plant & Equipment (Net) was $28.18 million in FY2024 (-4.5%), $29.5 million in FY2023 (+2.4%), $28.81 million in FY2022 (-1.3%) and $29.2 million in FY2021 (-5.1%).
- Quarterly Property, Plant & Equipment (Net) has run from a low of $27.33 million in Q3 2025 to a high of $29.58 million in Q3 2021 over five years.
- On a year-over-year basis, Property, Plant & Equipment (Net) has declined in each of the last nine quarters, with an average decline of 2.9% over the last eight quarters.
- The strongest year-over-year quarter for Property, Plant & Equipment (Net) in the past five years was Q3 2023, with growth of 2.8%; the weakest was Q4 2021, with a decline of 5.1%.
- According to Business Quant data, Property, Plant & Equipment (Net) for the three prior quarters was $27.38 million (Q1 2026), $27.41 million (Q4 2025) and $27.33 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | PP&E (Net) (Qtr) |
|---|---|---|---|---|---|
| 1 | Nike | 50.34 Bn | 16.54 Bn | 4.80 Bn | 4.89 Bn |
| 2 | Tapestry | 23.66 Bn | 19.62 Bn | 1.56 Bn | 502.10 Mn |
| 3 | Ralph Lauren | 21.85 Bn | 13.95 Bn | 1.44 Bn | 1.05 Bn |
| 4 | Deckers Outdoor | 11.26 Bn | 4.14 Bn | - | 337.78 Mn |
| 5 | Lululemon Athletica | 10.07 Bn | 4.32 Bn | 1.46 Bn | 2.05 Bn |
| 6 | Levi Strauss | 7.67 Bn | 4.32 Bn | 979.10 Mn | 659.80 Mn |
| 7 | Gildan Activewear | 6.27 Bn | 5.26 Bn | 459.76 Mn | 1.32 Bn |
| 8 | Birkenstock Holding | 6.13 Bn | 4.43 Bn | 493.89 Mn | 472.48 Mn |
| 9 | Crocs | 5.68 Bn | 5.09 Bn | 700.71 Mn | 246.08 Mn |
| 10 | Weyco | 486.05 Mn | 128.72 Mn | 43.78 Mn | 27.67 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 27.67 Mn |
| Mar 31, 2026 | 27.38 Mn |
| Dec 31, 2025 | 27.41 Mn |
| Sep 30, 2025 | 27.33 Mn |
| Jun 30, 2025 | 27.78 Mn |
| Mar 31, 2025 | 28.08 Mn |
| Dec 31, 2024 | 28.18 Mn |
| Sep 30, 2024 | 28.54 Mn |
| Jun 30, 2024 | 28.57 Mn |
| Mar 31, 2024 | 28.97 Mn |
| Dec 31, 2023 | 29.50 Mn |
| Sep 30, 2023 | 29.34 Mn |
| Jun 30, 2023 | 28.87 Mn |
| Mar 31, 2023 | 28.79 Mn |
| Dec 31, 2022 | 28.81 Mn |
| Sep 30, 2022 | 28.55 Mn |
| Jun 30, 2022 | 28.63 Mn |
| Mar 31, 2022 | 28.99 Mn |
| Dec 31, 2021 | 29.20 Mn |
| Sep 30, 2021 | 29.58 Mn |
Weyco Property, Plant & Equipment (Net) 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=property-plant-and-equipment-net&ticker=WEYS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "property-plant-and-equipment-net", "ticker": "WEYS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=property-plant-and-equipment-net&ticker=WEYS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();