Codexis (CDXS) Long-Term Debt Repayments (2017 - 2020)
Codexis' Long-Term Debt Repayments came in at $60,000 for FY2020, down 75.2% from $242,000 in FY2019.
Powered by 
Analysis
Codexis (CDXS) Long-Term Debt Repayments (2017 - 2020) Analysis & Trends
Going back to FY2017, Codexis' Long-Term Debt Repayments data covers 4 years.
- Long-Term Debt Repayments carries a three-year compound annual growth rate of -30.0% (FY2017 to FY2020).
- Per Business Quant, earlier years put Long-Term Debt Repayments at $242,000 in FY2019 (+1.7%), $238,000 in FY2018 (+36.0%) and $175,000 in FY2017.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | LT Debt Repayment (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 251.81 Bn | 230.84 Bn | 4.88 Bn | - |
| 2 | Abbott Laboratories | 177.61 Bn | 148.04 Bn | 7.27 Bn | 1.41 Bn |
| 3 | Danaher | 161.07 Bn | 144.87 Bn | 3.61 Bn | - |
| 4 | Intuitive Surgical | 156.01 Bn | 135.43 Bn | 1.96 Bn | - |
| 5 | Medtronic | 122.39 Bn | 87.64 Bn | 6.34 Bn | - |
| 6 | Stryker | 117.91 Bn | 104.03 Bn | 4.50 Bn | - |
| 7 | Boston Scientific | 66.91 Bn | 61.68 Bn | 3.85 Bn | - |
| 8 | Becton Dickinson | 54.47 Bn | 51.62 Bn | 2.32 Bn | 2.00 Bn |
| 9 | Edwards Lifesciences | 51.46 Bn | 35.47 Bn | 1.35 Bn | - |
| 10 | Codexis | 118.82 Mn | -138.22 Mn | 11.40 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2020 | 9,000.00 |
| Mar 31, 2020 | 51,000.00 |
| Dec 31, 2019 | 62,000.00 |
| Sep 30, 2019 | 61,000.00 |
| Jun 30, 2019 | 60,000.00 |
| Mar 31, 2019 | 59,000.00 |
| Dec 31, 2018 | 60,000.00 |
| Sep 30, 2018 | 60,000.00 |
| Jun 30, 2018 | 60,000.00 |
| Mar 31, 2018 | 58,000.00 |
| Dec 31, 2017 | 58,000.00 |
| Sep 30, 2017 | 57,000.00 |
| Jun 30, 2017 | 50,000.00 |
| Mar 31, 2017 | 10,000.00 |
API Access
Codexis Long-Term Debt Repayments 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=long-term-debt-repayments&ticker=CDXS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "long-term-debt-repayments", "ticker": "CDXS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=long-term-debt-repayments&ticker=CDXS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();