Wabash National (WNC) Price to Earnings (2011 - 2025)
Wabash National's (WNC) Price to Earnings was 1.65 for Q4 2025, up 7.7% from the prior quarter.
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Analysis
Wabash National (WNC) Price to Earnings (2011 - 2025) Analysis & Trends
Dating back to Q2 2011, Wabash National's Price to Earnings record includes 51 quarters.
- By year, Price to Earnings came in at 5.03 in FY2023 (-47.6%), 9.60 in FY2022 (-98.8%) and 820.95 in FY2021.
- The Q4 2025 figure ranks as the highest quarterly Price to Earnings since Q2 2024.
- The high point for year-over-year Price to Earnings in five years was Q2 2024 (growth of 6.4%); the low point was Q4 2022 (a decline of 98.8%).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Caterpillar | 388.70 Bn | 360.40 Bn | 7.76 Bn |
| 2 | Amphenol | 214.42 Bn | 209.12 Bn | 3.55 Bn |
| 3 | Deere | 185.30 Bn | 194.07 Bn | 4.66 Bn |
| 4 | Eaton | 169.35 Bn | 166.59 Bn | 2.86 Bn |
| 5 | Parker-Hannifin | 122.64 Bn | 120.77 Bn | 2.25 Bn |
| 6 | Vertiv Holdings | 97.12 Bn | 87.74 Bn | 1.23 Bn |
| 7 | Emerson Electric | 90.13 Bn | 82.89 Bn | 2.66 Bn |
| 8 | 3M | 83.49 Bn | 64.94 Bn | 2.68 Bn |
| 9 | Illinois Tool Works | 74.89 Bn | 71.45 Bn | 1.90 Bn |
| 10 | Wabash National | 572.36 Mn | 335.23 Mn | 15.33 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2025 | 1.65 |
| Sep 30, 2025 | 1.54 |
| Jun 30, 2024 | 6.32 |
| Mar 31, 2024 | 6.82 |
| Dec 31, 2023 | 5.03 |
| Sep 30, 2023 | 4.40 |
| Jun 30, 2023 | 5.94 |
| Mar 31, 2023 | 7.74 |
| Dec 31, 2022 | 9.60 |
| Sep 30, 2022 | 16.44 |
| Jun 30, 2022 | 32.55 |
| Mar 31, 2022 | 72.61 |
| Dec 31, 2021 | 820.95 |
| Sep 30, 2021 | 23.46 |
| Jun 30, 2021 | 32.49 |
| Mar 31, 2021 | 78.07 |
| Dec 31, 2019 | 8.77 |
| Sep 30, 2019 | 9.49 |
| Jun 30, 2019 | 14.35 |
| Mar 31, 2019 | 11.93 |
API Access
Wabash National 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=WNC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "price-to-earnings", "ticker": "WNC", "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=WNC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();