Wolverine World Wide (WWW) Price to Earnings (2010 - 2026)
Wolverine World Wide's Price to Earnings came in at 11.81 for Q2 2027, down 33.2% from 17.67 a year earlier.
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Analysis
Wolverine World Wide (WWW) Price to Earnings (2010 - 2026) Analysis & Trends
For FY2026, Wolverine World Wide's Price to Earnings was 15.46.
- Going back by year, Price to Earnings was 39.97 in FY2024.
- The Q2 2027 figure represents the lowest quarterly Price to Earnings in data going back to Q2 2011.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Nike | 50.34 Bn | 16.54 Bn | 4.80 Bn |
| 2 | Tapestry | 23.66 Bn | 19.62 Bn | 1.56 Bn |
| 3 | Ralph Lauren | 21.85 Bn | 13.95 Bn | 1.44 Bn |
| 4 | Deckers Outdoor | 11.26 Bn | 4.14 Bn | - |
| 5 | Lululemon Athletica | 10.07 Bn | 4.32 Bn | 1.46 Bn |
| 6 | Levi Strauss | 7.67 Bn | 4.32 Bn | 979.10 Mn |
| 7 | Gildan Activewear | 6.27 Bn | 5.26 Bn | 459.76 Mn |
| 8 | Birkenstock Holding | 6.13 Bn | 4.43 Bn | 493.89 Mn |
| 9 | Crocs | 5.68 Bn | 5.09 Bn | 700.71 Mn |
| 10 | Wolverine World Wide | 1.58 Bn | 955.17 Mn | 235.30 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 4, 2026 | 11.81 |
| Jan 3, 2026 | 15.46 |
| Sep 27, 2025 | 26.24 |
| Jun 28, 2025 | 17.67 |
| Mar 29, 2025 | 15.43 |
| Dec 28, 2024 | 39.97 |
| Oct 1, 2022 | 5.84 |
| Jul 2, 2022 | 9.31 |
| Apr 2, 2022 | 20.15 |
| Jan 1, 2022 | 20.01 |
| Sep 26, 2020 | 64.88 |
| Jun 27, 2020 | 29.76 |
| Mar 28, 2020 | 12.34 |
| Dec 28, 2019 | 21.51 |
| Sep 28, 2019 | 13.58 |
| Jun 29, 2019 | 13.13 |
| Mar 30, 2019 | 16.35 |
| Dec 29, 2018 | 14.82 |
| Sep 29, 2018 | 36.85 |
| Jun 30, 2018 | 50.94 |
API Access
Wolverine World Wide Price to Earnings 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=price-to-earnings&ticker=WWW&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "price-to-earnings", "ticker": "WWW", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=price-to-earnings&ticker=WWW&period=max&api_key=YOUR_API_KEY");
const data = await res.json();