Abbott Laboratories (ABT) Selling, General & Administrative (2009 - 2026)
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Analysis
Abbott Laboratories (ABT) Selling, General & Administrative (2009 - 2026) Analysis & Trends
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | SG&A (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 259.20 Bn | 235.84 Bn | 5.13 Bn | 2.32 Bn |
| 2 | Abbott Laboratories | 185.80 Bn | 160.26 Bn | 7.39 Bn | 4.27 Bn |
| 3 | Danaher | 162.28 Bn | 141.94 Bn | 3.84 Bn | 2.16 Bn |
| 4 | Intuitive Surgical | 155.44 Bn | 135.73 Bn | 2.08 Bn | 633.40 Mn |
| 5 | Medtronic | 132.01 Bn | 97.52 Bn | 6.34 Bn | 3.20 Bn |
| 6 | Stryker | 119.74 Bn | 105.93 Bn | 4.25 Bn | 2.31 Bn |
| 7 | Boston Scientific | 64.30 Bn | 59.73 Bn | 3.43 Bn | 1.68 Bn |
| 8 | Edwards Lifesciences | 61.70 Bn | 44.90 Bn | 1.35 Bn | 560.90 Mn |
| 9 | Agilent Technologies | 48.79 Bn | 41.68 Bn | 1.04 Bn | 475.00 Mn |
| 10 | GE HealthCare Technologies | 37.39 Bn | 25.63 Bn | 2.22 Bn | 1.10 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 4.27 Bn |
| Jun 30, 2026 | 4.03 Bn |
| Mar 31, 2026 | 3.74 Bn |
| Dec 31, 2025 | 3.13 Bn |
| Sep 30, 2025 | 3.05 Bn |
| Jun 30, 2025 | 3.09 Bn |
| Mar 31, 2025 | 3.06 Bn |
| Dec 31, 2024 | 2.91 Bn |
| Sep 30, 2024 | 2.90 Bn |
| Jun 30, 2024 | 2.94 Bn |
| Mar 31, 2024 | 2.96 Bn |
| Dec 31, 2023 | 2.72 Bn |
| Sep 30, 2023 | 2.72 Bn |
| Jun 30, 2023 | 2.74 Bn |
| Mar 31, 2023 | 2.76 Bn |
| Dec 31, 2022 | 2.97 Bn |
| Sep 30, 2022 | 2.73 Bn |
| Jun 30, 2022 | 2.76 Bn |
| Mar 31, 2022 | 2.79 Bn |
| Dec 31, 2021 | 3.05 Bn |
API Access
Abbott Laboratories Selling, General & Administrative 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=selling-general-and-administrative&ticker=ABT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "selling-general-and-administrative", "ticker": "ABT", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=selling-general-and-administrative&ticker=ABT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();