Co-Diagnostics (CODX) Non-Current Assets (2016 - 2026)
Co-Diagnostics (CODX) recorded Non-Current Assets of $10.85 million in Q3 2026, down 64.6% from $30.69 million a year earlier and down 4.8% from the prior quarter.
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Analysis
Co-Diagnostics (CODX) Non-Current Assets (2016 - 2026) Analysis & Trends
At the end of FY2025, Co-Diagnostics reported Non-Current Assets of $11.05 million, down 64.7% from FY2024.
- Annual Non-Current Assets has a five-year compound annual growth rate of 26.4% (FY2020 to FY2025).
- Across earlier years, Non-Current Assets came in at $31.27 million in FY2024 (-5.8%), $33.18 million in FY2023 (+9.3%), $30.35 million in FY2022 (-32.4%) and $44.91 million in FY2021.
- The Q3 2026 figure is the lowest quarterly Non-Current Assets since Q3 2021.
- On a year-over-year basis, Non-Current Assets has declined for ten consecutive quarters, with an average decline of 34.4% over the last eight quarters.
- Peak year-over-year performance for Non-Current Assets in the last five years was growth of 9.3% in Q4 2023, against a decline of 64.7% in Q4 2025 at the low end.
- Per Business Quant, the preceding three quarters came in at $11.4 million (Q2 2026), $11.72 million (Q1 2026) and $11.05 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Non-Current Assets (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 259.44 Bn | 236.08 Bn | 5.13 Bn | 88.62 Bn |
| 2 | Abbott Laboratories | 187.98 Bn | 162.45 Bn | 7.39 Bn | 84.75 Bn |
| 3 | Danaher | 163.91 Bn | 143.58 Bn | 3.84 Bn | 78.49 Bn |
| 4 | Intuitive Surgical | 153.75 Bn | 134.17 Bn | 2.08 Bn | 10.92 Bn |
| 5 | Medtronic | 131.67 Bn | 97.80 Bn | 6.34 Bn | 68.92 Bn |
| 6 | Stryker | 117.84 Bn | 104.03 Bn | 4.25 Bn | 33.06 Bn |
| 7 | Boston Scientific | 64.27 Bn | 59.95 Bn | 3.43 Bn | 37.30 Bn |
| 8 | Edwards Lifesciences | 61.69 Bn | 45.00 Bn | 1.35 Bn | 6.90 Bn |
| 9 | Medline | 51.94 Bn | 49.07 Bn | 1.93 Bn | 27.53 Bn |
| 10 | Co-Diagnostics | 1.90 Mn | -22.58 Mn | -20,463.00 | 10.85 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 10.85 Mn |
| Jun 30, 2026 | 11.40 Mn |
| Mar 31, 2026 | 11.72 Mn |
| Dec 31, 2025 | 11.05 Mn |
| Sep 30, 2025 | 30.69 Mn |
| Jun 30, 2025 | 31.16 Mn |
| Mar 31, 2025 | 31.32 Mn |
| Dec 31, 2024 | 31.27 Mn |
| Sep 30, 2024 | 32.28 Mn |
| Jun 30, 2024 | 32.48 Mn |
| Mar 31, 2024 | 32.97 Mn |
| Dec 31, 2023 | 33.18 Mn |
| Sep 30, 2023 | 37.37 Mn |
| Jun 30, 2023 | 35.42 Mn |
| Mar 31, 2023 | 31.07 Mn |
| Dec 31, 2022 | 30.35 Mn |
| Sep 30, 2022 | 45.93 Mn |
| Jun 30, 2022 | 46.27 Mn |
| Mar 31, 2022 | 45.81 Mn |
| Dec 31, 2021 | 44.91 Mn |
API Access
Co-Diagnostics Non-Current Assets 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=non-current-assets&ticker=CODX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "non-current-assets", "ticker": "CODX", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=non-current-assets&ticker=CODX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();