Agilent Technologies (A) Net of Acquisitions & Divestments (2009 - 2026)
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Analysis
Agilent Technologies (A) Net of Acquisitions & Divestments (2009 - 2026) Analysis & Trends
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Net Acquisitions (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 257.79 Bn | 234.30 Bn | 5.13 Bn | -5.00 Mn |
| 2 | Abbott Laboratories | 190.83 Bn | 164.70 Bn | 7.39 Bn | -121.00 Mn |
| 3 | Danaher | 162.10 Bn | 141.75 Bn | 3.84 Bn | -38.00 Mn |
| 4 | Intuitive Surgical | 158.05 Bn | 138.34 Bn | 2.08 Bn | 9.60 Mn |
| 5 | Medtronic | 130.31 Bn | 95.56 Bn | 6.34 Bn | -1.16 Bn |
| 6 | Stryker | 124.76 Bn | 110.95 Bn | 4.25 Bn | -22.00 Mn |
| 7 | Boston Scientific | 62.03 Bn | 57.46 Bn | 3.43 Bn | -212.00 Mn |
| 8 | Edwards Lifesciences | 58.73 Bn | 41.94 Bn | 1.35 Bn | -4.30 Mn |
| 9 | Becton Dickinson | 58.33 Bn | 55.48 Bn | 2.32 Bn | -22.00 Mn |
| 10 | Agilent Technologies | 49.29 Bn | 42.18 Bn | 1.04 Bn | -950.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | -950.00 Mn |
| Jan 31, 2025 | 4.00 Mn |
| Oct 31, 2024 | -859.00 Mn |
| Jul 31, 2024 | -3.00 Mn |
| Apr 30, 2023 | -21.00 Mn |
| Jan 31, 2023 | -30.00 Mn |
| Oct 31, 2022 | -34.00 Mn |
| Apr 30, 2022 | -18.00 Mn |
| Oct 31, 2019 | -1.16 Bn |
| Jan 31, 2019 | -248.00 Mn |
| Oct 31, 2018 | -79.00 Mn |
| Jul 31, 2018 | -430.00 Mn |
| Apr 30, 2018 | -1.00 Mn |
| Jan 31, 2018 | -6.00 Mn |
| Jul 31, 2017 | -57.00 Mn |
| Jan 31, 2017 | -69.00 Mn |
| Oct 31, 2016 | -26.00 Mn |
| Jan 31, 2016 | -235.00 Mn |
| Oct 31, 2015 | -8.00 Mn |
| Jul 31, 2015 | -66.00 Mn |
API Access
Agilent Technologies Net of Acquisitions & Divestments 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=net-of-acquisitions-and-divestments&ticker=A&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "net-of-acquisitions-and-divestments", "ticker": "A", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=net-of-acquisitions-and-divestments&ticker=A&period=max&api_key=YOUR_API_KEY");
const data = await res.json();