Codexis (CDXS) Receivables (2010 - 2026)
Codexis (CDXS) posted Receivables of $13.03 million for Q2 2026, down 34.2% from $19.8 million a year earlier but up 39.8% from the prior quarter.
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Analysis
Codexis (CDXS) Receivables (2010 - 2026) Analysis & Trends
At the end of FY2025, Codexis' Receivables came in at $12.43 million, down 43.7% from FY2024.
- Annual Receivables has declined for three consecutive years, with a five-year compound annual growth rate of -20.9% (FY2020 to FY2025).
- In prior years, Codexis' Receivables was $22.09 million in FY2024 (-25.9%), $29.83 million in FY2023 (-37.7%), $47.89 million in FY2022 (+3.6%) and $46.21 million in FY2021 (+14.9%).
- Quarterly Receivables has run from a low of $9.32 million in Q1 2026 to a high of $59.23 million in Q3 2021 over five years.
- On a year-over-year basis, Receivables has declined in each of the last four quarters, with an average decline of 27.1% over the last eight quarters.
- The strongest year-over-year quarter for Receivables in the past five years was Q3 2021, with growth of 42.4%; the weakest was Q1 2023, with a decline of 48.2%.
- According to Business Quant data, Receivables for the three prior quarters was $9.32 million (Q1 2026), $12.43 million (Q4 2025) and $11.73 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Receivables (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 250.84 Bn | 229.99 Bn | 4.88 Bn | 11.14 Bn |
| 2 | Abbott Laboratories | 174.73 Bn | 145.82 Bn | 7.27 Bn | 8.60 Bn |
| 3 | Danaher | 159.85 Bn | 143.67 Bn | 3.61 Bn | 3.97 Bn |
| 4 | Intuitive Surgical | 146.79 Bn | 126.35 Bn | 1.96 Bn | 1.67 Bn |
| 5 | Medtronic | 114.54 Bn | 80.41 Bn | 6.34 Bn | 6.36 Bn |
| 6 | Stryker | 105.67 Bn | 91.79 Bn | 4.50 Bn | 3.74 Bn |
| 7 | Boston Scientific | 63.93 Bn | 58.94 Bn | 3.85 Bn | 3.05 Bn |
| 8 | Becton Dickinson | 50.12 Bn | 47.27 Bn | 2.32 Bn | 2.36 Bn |
| 9 | Edwards Lifesciences | 50.06 Bn | 34.17 Bn | 1.35 Bn | 955.70 Mn |
| 10 | Codexis | 124.29 Mn | -132.76 Mn | 11.40 Mn | 13.03 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 13.03 Mn |
| Mar 31, 2026 | 9.32 Mn |
| Dec 31, 2025 | 12.43 Mn |
| Sep 30, 2025 | 11.73 Mn |
| Jun 30, 2025 | 19.80 Mn |
| Mar 31, 2025 | 15.44 Mn |
| Dec 31, 2024 | 22.09 Mn |
| Sep 30, 2024 | 21.33 Mn |
| Jun 30, 2024 | 17.93 Mn |
| Mar 31, 2024 | 20.58 Mn |
| Dec 31, 2023 | 29.83 Mn |
| Sep 30, 2023 | 24.75 Mn |
| Jun 30, 2023 | 32.30 Mn |
| Mar 31, 2023 | 27.81 Mn |
| Dec 31, 2022 | 47.89 Mn |
| Sep 30, 2022 | 37.27 Mn |
| Jun 30, 2022 | 57.46 Mn |
| Mar 31, 2022 | 53.70 Mn |
| Dec 31, 2021 | 46.21 Mn |
| Sep 30, 2021 | 59.23 Mn |
API Access
Codexis Receivables 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=receivables&ticker=CDXS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "receivables", "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=receivables&ticker=CDXS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();