Co-Diagnostics (CODX) Total Liabilities (2016 - 2026)
Co-Diagnostics' Total Liabilities was $3.37 million in Q3 2026, down 37.1% from $5.35 million a year earlier and down 13.2% from the prior quarter.
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Analysis
Co-Diagnostics (CODX) Total Liabilities (2016 - 2026) Analysis & Trends
At the end of FY2025, Total Liabilities at Co-Diagnostics came in at $4.11 million, down 57.5% from FY2024.
- Total Liabilities shows a five-year compound annual growth rate of -2.0% (FY2020 to FY2025).
- In earlier years, Total Liabilities was $9.69 million in FY2024 (-0.6%), $9.74 million in FY2023 (+13.7%), $8.57 million in FY2022 (-66.5%) and $25.56 million in FY2021 (+462.9%).
- The Q3 2026 figure marks the lowest quarterly Total Liabilities since Q3 2020.
- Compared with a year earlier, Total Liabilities has declined for ten straight quarters, with an average decline of 29.1% over the last eight quarters.
- The best year-over-year quarter for Total Liabilities over five years was Q4 2021 (growth of 462.9%); the worst was Q1 2023 (a decline of 72.8%).
- Per Business Quant data, CODX's Total Liabilities in the three quarters before Q3 2026 was $3.88 million (Q2 2026), $5.46 million (Q1 2026) and $4.11 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 259.44 Bn | 236.08 Bn | 5.13 Bn | 59.47 Bn |
| 2 | Abbott Laboratories | 187.98 Bn | 162.45 Bn | 7.39 Bn | 56.62 Bn |
| 3 | Danaher | 163.91 Bn | 143.58 Bn | 3.84 Bn | 39.65 Bn |
| 4 | Intuitive Surgical | 153.75 Bn | 134.17 Bn | 2.08 Bn | 3.23 Bn |
| 5 | Medtronic | 131.67 Bn | 97.80 Bn | 6.34 Bn | 42.46 Bn |
| 6 | Stryker | 117.84 Bn | 104.03 Bn | 4.25 Bn | 23.79 Bn |
| 7 | Boston Scientific | 64.27 Bn | 59.95 Bn | 3.43 Bn | 19.59 Bn |
| 8 | Edwards Lifesciences | 61.69 Bn | 45.00 Bn | 1.35 Bn | 3.18 Bn |
| 9 | Medline | 51.94 Bn | 49.07 Bn | 1.93 Bn | 20.79 Bn |
| 10 | Co-Diagnostics | 1.90 Mn | -22.58 Mn | -20,463.00 | 3.37 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 3.37 Mn |
| Jun 30, 2026 | 3.88 Mn |
| Mar 31, 2026 | 5.46 Mn |
| Dec 31, 2025 | 4.11 Mn |
| Sep 30, 2025 | 5.35 Mn |
| Jun 30, 2025 | 5.76 Mn |
| Mar 31, 2025 | 7.67 Mn |
| Dec 31, 2024 | 9.69 Mn |
| Sep 30, 2024 | 8.60 Mn |
| Jun 30, 2024 | 8.30 Mn |
| Mar 31, 2024 | 8.32 Mn |
| Dec 31, 2023 | 9.74 Mn |
| Sep 30, 2023 | 9.19 Mn |
| Jun 30, 2023 | 9.37 Mn |
| Mar 31, 2023 | 6.37 Mn |
| Dec 31, 2022 | 8.57 Mn |
| Sep 30, 2022 | 12.90 Mn |
| Jun 30, 2022 | 16.37 Mn |
| Mar 31, 2022 | 23.44 Mn |
| Dec 31, 2021 | 25.56 Mn |
API Access
Co-Diagnostics Total Liabilities 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=total-liabilities&ticker=CODX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "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=total-liabilities&ticker=CODX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();