Codexis (CDXS) Return on Sales [ROS] (2009 - 2026)
Codexis (CDXS) recorded Return on Sales [ROS] of -38.60% in Q3 2026, up 181.71 percentage points from -220.31% a year earlier and up 36.68 percentage points from the prior quarter.
Codexis (CDXS) Return on Sales [ROS] (2009 - 2026) Analysis & Trends
On a TTM basis, Codexis' Return on Sales [ROS] came in at -18.28% as of Sep 30, 2026, up 94.39 percentage points year-over-year; for FY2025, it was -59.30%, up 39.31 percentage points from FY2024.
- Annual Return on Sales [ROS] has a five-year change of -24.66 percentage points (FY2020 to FY2025).
- Across earlier years, Return on Sales [ROS] came in at -98.61% in FY2024 (-1.56 pp), -97.04% in FY2023 (-71.87 pp), -25.17% in FY2022 (-3.50 pp) and -21.67% in FY2021 (+12.97 pp).
- Quarterly Return on Sales [ROS] has ranged from -345.59% in Q3 2023 to 27.13% in Q4 2025 over the past five years.
- On a year-over-year basis, Return on Sales [ROS] has increased for four consecutive quarters, with an average year-over-year change of +42.87 percentage points over the last eight quarters.
- Peak year-over-year performance for Return on Sales [ROS] in the last five years was a gain of 218.84 percentage points in Q1 2026, against a drop of 314.73 percentage points in Q3 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at -75.29% (Q2 2026), -52.75% (Q1 2026) and 27.13% (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 259.44 Bn | 236.08 Bn | 5.13 Bn | 18.65% |
| 2 | Abbott Laboratories | 187.98 Bn | 162.45 Bn | 7.39 Bn | 10.44% |
| 3 | Danaher | 163.91 Bn | 143.58 Bn | 3.84 Bn | 19.00% |
| 4 | Intuitive Surgical | 153.75 Bn | 134.17 Bn | 2.08 Bn | 19.44% |
| 5 | Medtronic | 131.67 Bn | 97.80 Bn | 6.34 Bn | 18.08% |
| 6 | Stryker | 117.84 Bn | 104.03 Bn | 4.25 Bn | 15.86% |
| 7 | Boston Scientific | 64.27 Bn | 59.95 Bn | 3.43 Bn | 16.12% |
| 8 | Edwards Lifesciences | 61.69 Bn | 45.00 Bn | 1.35 Bn | 17.44% |
| 9 | Medline | 51.94 Bn | 49.07 Bn | 1.93 Bn | 6.36% |
| 10 | Codexis | 127.04 Mn | -143.91 Mn | 15.25 Mn | -38.60% |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | -38.60% |
| Jun 30, 2026 | -75.29% |
| Mar 31, 2026 | -52.75% |
| Dec 31, 2025 | 27.13% |
| Sep 30, 2025 | -220.31% |
| Jun 30, 2025 | -83.91% |
| Mar 31, 2025 | -271.59% |
| Dec 31, 2024 | -34.21% |
| Sep 30, 2024 | -129.02% |
| Jun 30, 2024 | -284.90% |
| Mar 31, 2024 | -69.63% |
| Dec 31, 2023 | 1.06% |
| Sep 30, 2023 | -345.59% |
| Jun 30, 2023 | -59.21% |
| Mar 31, 2023 | -182.29% |
| Dec 31, 2022 | -43.62% |
| Sep 30, 2022 | -30.86% |
| Jun 30, 2022 | -6.79% |
| Mar 31, 2022 | -23.73% |
| Dec 31, 2021 | -42.39% |
Codexis Return on Sales [ROS] 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=return-on-sales-%5Bros%5D&ticker=CDXS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "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=return-on-sales-%5Bros%5D&ticker=CDXS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();