Worksport (WKSP) Price to Earnings (2014)
Worksport's (WKSP) Price to Earnings came in at 2188.13 for Q1 2014.
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Analysis
Worksport (WKSP) Price to Earnings (2014) Analysis & Trends
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Tesla | 1,199.60 Bn | 1,034.16 Bn | 4.75 Bn |
| 2 | Toyota Motor | 237.87 Bn | -168.87 Bn | 20.95 Bn |
| 3 | Ferrari | 144.10 Bn | 136.55 Bn | 1.18 Bn |
| 4 | Honda Motor | 142.11 Bn | 9.49 Bn | 8.46 Bn |
| 5 | General Motors | 68.70 Bn | -36.17 Bn | 7.33 Bn |
| 6 | Ford Motor | 47.39 Bn | -95.07 Bn | 6.08 Bn |
| 7 | Rivian Automotive | 19.48 Bn | -3.81 Bn | 179.00 Mn |
| 8 | Magna International | 18.09 Bn | 15.65 Bn | 1.61 Bn |
| 9 | Stellantis | 12.78 Bn | -153.22 Bn | 5.55 Bn |
| 10 | Worksport | 5.45 Mn | -5.98 Mn | 1.65 Mn |
API Access
Worksport 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=WKSP&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "price-to-earnings", "ticker": "WKSP", "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=WKSP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();