Co-Diagnostics (CODX) Operating Expenses (2016 - 2026)
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Analysis
Co-Diagnostics (CODX) Operating Expenses (2016 - 2026) Analysis & Trends
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 241.25 Bn | 220.40 Bn | 4.88 Bn | 9.91 Bn |
| 2 | Abbott Laboratories | 167.33 Bn | 138.41 Bn | 7.27 Bn | 10.90 Bn |
| 3 | Danaher | 148.83 Bn | 132.65 Bn | 3.61 Bn | 2.48 Bn |
| 4 | Intuitive Surgical | 142.00 Bn | 121.55 Bn | 1.96 Bn | 988.50 Mn |
| 5 | Medtronic | 110.70 Bn | 76.57 Bn | 6.34 Bn | 4.06 Bn |
| 6 | Stryker | 104.72 Bn | 90.84 Bn | 4.50 Bn | 2.84 Bn |
| 7 | Boston Scientific | 62.66 Bn | 57.67 Bn | 3.85 Bn | 2.67 Bn |
| 8 | Edwards Lifesciences | 49.13 Bn | 33.24 Bn | 1.35 Bn | 840.10 Mn |
| 9 | Becton Dickinson | 48.51 Bn | 45.66 Bn | 2.32 Bn | 4.32 Bn |
| 10 | Co-Diagnostics | 4.65 Mn | 4.65 Mn | 120,828.00 | 6.32 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 6.32 Mn |
| Dec 31, 2025 | 26.66 Mn |
| Sep 30, 2025 | 7.13 Mn |
| Jun 30, 2025 | 8.19 Mn |
| Mar 31, 2025 | 8.58 Mn |
| Dec 31, 2024 | 11.80 Mn |
| Sep 30, 2024 | 10.58 Mn |
| Jun 30, 2024 | 10.12 Mn |
| Mar 31, 2024 | 10.49 Mn |
| Dec 31, 2023 | 12.41 Mn |
| Sep 30, 2023 | 11.14 Mn |
| Jun 30, 2023 | 11.73 Mn |
| Mar 31, 2023 | 10.05 Mn |
| Dec 31, 2022 | 27.01 Mn |
| Sep 30, 2022 | 10.86 Mn |
| Jun 30, 2022 | 8.25 Mn |
| Mar 31, 2022 | 9.59 Mn |
| Dec 31, 2021 | 7.61 Mn |
| Sep 30, 2021 | 13.16 Mn |
| Jun 30, 2021 | 13.06 Mn |
API Access
Co-Diagnostics Operating Expenses 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=operating-expenses&ticker=CODX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "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=operating-expenses&ticker=CODX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();