Conmed (CNMD) Amortizatization of Intangibles (2010 - 2019)
Conmed's Amortizatization of Intangibles was $12.26 million in Q4 2019, up 23.8% from $9.9 million a year earlier but down 14.2% from the prior quarter.
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Analysis
Conmed (CNMD) Amortizatization of Intangibles (2010 - 2019) Analysis & Trends
For FY2019, Amortizatization of Intangibles at Conmed came in at $53.64 million, up 27.0% from FY2018.
- Amortizatization of Intangibles has now increased for four consecutive years, with a five-year compound annual growth rate of 15.6% (FY2014 to FY2019).
- In earlier years, Amortizatization of Intangibles was $42.23 million in FY2018 (+12.8%), $37.43 million in FY2017 (+7.5%), $34.83 million in FY2016 (+38.4%) and $25.18 million in FY2015 (-3.0%).
- Quarterly Amortizatization of Intangibles has moved between $5.54 million (Q1 2015) and $14.3 million (Q3 2019) over five years.
- Compared with a year earlier, Amortizatization of Intangibles has increased for 18 straight quarters, with growth averaging 19.9% over the last eight quarters.
- The best year-over-year quarter for Amortizatization of Intangibles over five years was Q1 2016 (growth of 49.4%); the worst was Q1 2015 (a decline of 12.1%).
- Per Business Quant data, CNMD's Amortizatization of Intangibles in the three quarters before Q4 2019 was $14.3 million (Q3 2019), $14.17 million (Q2 2019) and $12.91 million (Q1 2019).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Amort. of Intangibles (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 242.18 Bn | 221.33 Bn | 4.88 Bn | 485.00 Mn |
| 2 | Abbott Laboratories | 168.71 Bn | 139.79 Bn | 7.27 Bn | 658.00 Mn |
| 3 | Danaher | 150.46 Bn | 134.27 Bn | 3.61 Bn | 463.00 Mn |
| 4 | Intuitive Surgical | 138.71 Bn | 118.26 Bn | 1.96 Bn | 24.00 Mn |
| 5 | Medtronic | 110.54 Bn | 76.41 Bn | 6.34 Bn | - |
| 6 | Stryker | 105.66 Bn | 91.78 Bn | 4.50 Bn | 175.00 Mn |
| 7 | Boston Scientific | 61.74 Bn | 56.75 Bn | 3.85 Bn | - |
| 8 | Edwards Lifesciences | 49.09 Bn | 33.21 Bn | 1.35 Bn | - |
| 9 | Becton Dickinson | 48.16 Bn | 45.31 Bn | 2.32 Bn | - |
| 10 | Conmed | 1.39 Bn | 1.23 Bn | 197.46 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2019 | 12.26 Mn |
| Sep 30, 2019 | 14.30 Mn |
| Jun 30, 2019 | 14.17 Mn |
| Mar 31, 2019 | 12.91 Mn |
| Dec 31, 2018 | 9.90 Mn |
| Sep 30, 2018 | 10.84 Mn |
| Jun 30, 2018 | 10.74 Mn |
| Mar 31, 2018 | 10.75 Mn |
| Dec 31, 2017 | 9.36 Mn |
| Sep 30, 2017 | 9.63 Mn |
| Jun 30, 2017 | 9.38 Mn |
| Mar 31, 2017 | 9.06 Mn |
| Dec 31, 2016 | 8.86 Mn |
| Sep 30, 2016 | 8.62 Mn |
| Jun 30, 2016 | 9.08 Mn |
| Mar 31, 2016 | 8.27 Mn |
| Dec 31, 2015 | 6.79 Mn |
| Sep 30, 2015 | 6.50 Mn |
| Jun 30, 2015 | 6.35 Mn |
| Mar 31, 2015 | 5.54 Mn |
API Access
Conmed Amortizatization of Intangibles 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=amortizatization-of-intangibles&ticker=CNMD&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "amortizatization-of-intangibles", "ticker": "CNMD", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=amortizatization-of-intangibles&ticker=CNMD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();