Codexis (CDXS) Cash & Equivalents (2009 - 2026)
Codexis (CDXS) recorded Cash & Equivalents of $29.21 million in Q3 2026, up 15.2% from $25.35 million a year earlier and up 7.5% from the prior quarter.
Codexis (CDXS) Cash & Equivalents (2009 - 2026) Analysis & Trends
At the end of FY2025, Codexis reported Cash & Equivalents of $50.79 million, up 163.7% from FY2024.
- Annual Cash & Equivalents has a five-year compound annual growth rate of -19.4% (FY2020 to FY2025).
- Across earlier years, Cash & Equivalents came in at $19.26 million in FY2024 (-70.4%), $65.12 million in FY2023 (-42.9%), $113.98 million in FY2022 (-2.4%) and $116.8 million in FY2021 (-21.7%).
- Quarterly Cash & Equivalents has ranged from $18.32 million in Q1 2025 to $116.8 million in Q4 2021 over the past five years.
- On a year-over-year basis, Cash & Equivalents has increased for four consecutive quarters, with growth averaging 19.1% over the last eight quarters.
- Peak year-over-year performance for Cash & Equivalents in the last five years was growth of 163.7% in Q4 2025, against a decline of 79.8% in Q2 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at $27.17 million (Q2 2026), $36.57 million (Q1 2026) and $50.79 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cash & Equiv. (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 259.44 Bn | 236.08 Bn | 5.13 Bn | 5.46 Bn |
| 2 | Abbott Laboratories | 187.98 Bn | 162.45 Bn | 7.39 Bn | 4.05 Bn |
| 3 | Danaher | 163.91 Bn | 143.58 Bn | 3.84 Bn | 5.68 Bn |
| 4 | Intuitive Surgical | 153.75 Bn | 134.17 Bn | 2.08 Bn | 2.98 Bn |
| 5 | Medtronic | 131.67 Bn | 97.80 Bn | 6.34 Bn | 1.69 Bn |
| 6 | Stryker | 117.84 Bn | 104.03 Bn | 4.25 Bn | 3.27 Bn |
| 7 | Boston Scientific | 64.27 Bn | 59.95 Bn | 3.43 Bn | 609.00 Mn |
| 8 | Edwards Lifesciences | 61.69 Bn | 45.00 Bn | 1.35 Bn | 3.11 Bn |
| 9 | Medline | 51.94 Bn | 49.07 Bn | 1.93 Bn | 2.32 Bn |
| 10 | Codexis | 127.04 Mn | -143.91 Mn | 15.25 Mn | 29.21 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 29.21 Mn |
| Jun 30, 2026 | 27.17 Mn |
| Mar 31, 2026 | 36.57 Mn |
| Dec 31, 2025 | 50.79 Mn |
| Sep 30, 2025 | 25.35 Mn |
| Jun 30, 2025 | 26.76 Mn |
| Mar 31, 2025 | 18.32 Mn |
| Dec 31, 2024 | 19.26 Mn |
| Sep 30, 2024 | 37.45 Mn |
| Jun 30, 2024 | 18.60 Mn |
| Mar 31, 2024 | 58.05 Mn |
| Dec 31, 2023 | 65.12 Mn |
| Sep 30, 2023 | 74.58 Mn |
| Jun 30, 2023 | 92.09 Mn |
| Mar 31, 2023 | 102.83 Mn |
| Dec 31, 2022 | 113.98 Mn |
| Sep 30, 2022 | 108.69 Mn |
| Jun 30, 2022 | 90.11 Mn |
| Mar 31, 2022 | 94.26 Mn |
| Dec 31, 2021 | 116.80 Mn |
Codexis Cash & Equivalents 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=cash-and-equivalents&ticker=CDXS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cash-and-equivalents", "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=cash-and-equivalents&ticker=CDXS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();