Rocky Brands (RCKY) Property, Plant & Equipment (Net) (2010 - 2026)
Rocky Brands (RCKY) posted Property, Plant & Equipment (Net) of $52.36 million for Q2 2026, up 2.9% from $50.91 million a year earlier and up 4.2% from the prior quarter.
Rocky Brands (RCKY) Property, Plant & Equipment (Net) (2010 - 2026) Analysis & Trends
At the end of FY2025, Rocky Brands' Property, Plant & Equipment (Net) came in at $49.93 million, up 0.5% from FY2024.
- Annual Property, Plant & Equipment (Net) shows a five-year compound annual growth rate of 8.1% (FY2020 to FY2025).
- In prior years, Rocky Brands' Property, Plant & Equipment (Net) was $49.67 million in FY2024 (-4.4%), $51.98 million in FY2023 (-9.4%), $57.36 million in FY2022 (-4.4%) and $59.99 million in FY2021 (+77.7%).
- The Q2 2026 figure stands as the highest quarterly Property, Plant & Equipment (Net) since Q3 2023.
- On a year-over-year basis, Property, Plant & Equipment (Net) has increased in each of the last four quarters, with an average decline of 1.1% over the last eight quarters.
- The strongest year-over-year quarter for Property, Plant & Equipment (Net) in the past five years was Q3 2021, with growth of 82.6%; the weakest was Q2 2023, with a decline of 11.9%.
- According to Business Quant data, Property, Plant & Equipment (Net) for the three prior quarters was $50.23 million (Q1 2026), $49.93 million (Q4 2025) and $50.53 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 | Rocky Brands | 349.98 Mn | 339.47 Mn | 60.80 Mn | 52.36 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 52.36 Mn |
| Mar 31, 2026 | 50.23 Mn |
| Dec 31, 2025 | 49.93 Mn |
| Sep 30, 2025 | 50.53 Mn |
| Jun 30, 2025 | 50.91 Mn |
| Mar 31, 2025 | 49.59 Mn |
| Dec 31, 2024 | 49.67 Mn |
| Sep 30, 2024 | 50.38 Mn |
| Jun 30, 2024 | 51.30 Mn |
| Mar 31, 2024 | 51.31 Mn |
| Dec 31, 2023 | 51.98 Mn |
| Sep 30, 2023 | 53.12 Mn |
| Jun 30, 2023 | 54.03 Mn |
| Mar 31, 2023 | 54.67 Mn |
| Dec 31, 2022 | 57.36 Mn |
| Sep 30, 2022 | 60.27 Mn |
| Jun 30, 2022 | 61.35 Mn |
| Mar 31, 2022 | 60.96 Mn |
| Dec 31, 2021 | 59.99 Mn |
| Sep 30, 2021 | 57.19 Mn |
Rocky Brands 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=RCKY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "property-plant-and-equipment-net", "ticker": "RCKY", "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=RCKY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();