Angiodynamics (ANGO) Price to Earnings (2009 - 2023)
Angiodynamics' Price to Earnings came in at 50.10 for fiscal Q1 2024 (quarter ended Aug 31, 2023).
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Analysis
Angiodynamics (ANGO) Price to Earnings (2009 - 2023) Analysis & Trends
For FY2019 (ended May 31, 2019), Angiodynamics' Price to Earnings was 11.52, down 76.0% from FY2018.
- Going back by fiscal year, Price to Earnings was 47.92 in FY2018 (-56.8%) and 110.93 in FY2017.
- The fiscal Q1 2024 figure represents the highest quarterly Price to Earnings since fiscal Q3 2019.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 266.22 Bn | 242.86 Bn | 5.13 Bn |
| 2 | Abbott Laboratories | 191.31 Bn | 165.77 Bn | 7.39 Bn |
| 3 | Danaher | 166.16 Bn | 145.82 Bn | 3.84 Bn |
| 4 | Intuitive Surgical | 155.98 Bn | 136.40 Bn | 2.08 Bn |
| 5 | Medtronic | 130.05 Bn | 96.18 Bn | 6.34 Bn |
| 6 | Stryker | 123.40 Bn | 109.59 Bn | 4.25 Bn |
| 7 | Boston Scientific | 64.81 Bn | 60.48 Bn | 3.43 Bn |
| 8 | Edwards Lifesciences | 59.87 Bn | 43.18 Bn | 1.35 Bn |
| 9 | Medline | 53.84 Bn | 50.96 Bn | 1.93 Bn |
| 10 | Angiodynamics | 20.48 Mn | -146.80 Mn | 48.04 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 31, 2023 | 2.00 |
| Feb 29, 2020 | 0.36 |
| Nov 30, 2019 | 0.42 |
| Aug 31, 2019 | 0.46 |
| May 31, 2019 | 0.46 |
| Feb 28, 2019 | 7.37 |
| Nov 30, 2018 | 1.81 |
| Aug 31, 2018 | 2.11 |
| May 31, 2018 | 1.92 |
| Feb 28, 2018 | 18.35 |
| Aug 31, 2017 | 6.87 |
| May 31, 2017 | 4.44 |
| Nov 30, 2013 | 4.27 |
| Aug 31, 2013 | 4.38 |
| May 31, 2013 | 5.72 |
| Feb 29, 2012 | 12.70 |
| Nov 30, 2011 | 2.30 |
| Aug 31, 2011 | 1.92 |
| May 31, 2011 | 1.94 |
| Feb 28, 2011 | 1.32 |
API Access
Angiodynamics 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=ANGO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "price-to-earnings", "ticker": "ANGO", "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=ANGO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();