Codexis (CDXS) Return on Sales [ROS] (2010 - 2026)
Codexis (CDXS) recorded Return on Sales [ROS] of -75.29% in Q2 2026, up 8.63 percentage points from -83.91% a year earlier but down 22.54 percentage points from the prior quarter.
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Analysis
Codexis (CDXS) Return on Sales [ROS] (2010 - 2026) Analysis & Trends
On a TTM basis, Codexis' Return on Sales [ROS] came in at -35.61% as of Jun 30, 2026, up 64.53 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 three consecutive quarters, with an average year-over-year change of +47.23 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 -52.75% (Q1 2026), 27.13% (Q4 2025) and -220.31% (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 242.18 Bn | 221.33 Bn | 4.88 Bn | 17.40% |
| 2 | Abbott Laboratories | 168.71 Bn | 139.79 Bn | 7.27 Bn | 13.44% |
| 3 | Danaher | 150.46 Bn | 134.27 Bn | 3.61 Bn | 17.99% |
| 4 | Intuitive Surgical | 138.71 Bn | 118.26 Bn | 1.96 Bn | 33.60% |
| 5 | Medtronic | 110.54 Bn | 76.41 Bn | 6.34 Bn | 18.08% |
| 6 | Stryker | 105.66 Bn | 91.78 Bn | 4.50 Bn | 25.18% |
| 7 | Boston Scientific | 61.74 Bn | 56.75 Bn | 3.85 Bn | 21.65% |
| 8 | Edwards Lifesciences | 49.09 Bn | 33.21 Bn | 1.35 Bn | 29.48% |
| 9 | Becton Dickinson | 48.16 Bn | 45.31 Bn | 2.32 Bn | 13.31% |
| 10 | Codexis | 124.29 Mn | -132.76 Mn | 11.40 Mn | -75.29% |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| 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% |
| Sep 30, 2021 | 3.62% |
API Access
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_KEYimport 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();