International Flavors & Fragrances (IFF) Net of Acquisitions & Divestments (2014 - 2026)
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Analysis
International Flavors & Fragrances (IFF) Net of Acquisitions & Divestments (2014 - 2026) Analysis & Trends
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Net Acquisitions (Qtr) |
|---|---|---|---|---|---|
| 1 | Linde | 234.56 Bn | 217.67 Bn | 4.43 Bn | -221.00 Mn |
| 2 | Corning | 106.49 Bn | 99.63 Bn | 1.63 Bn | - |
| 3 | Sherwin Williams | 81.85 Bn | 80.89 Bn | 3.34 Bn | -64.90 Mn |
| 4 | Air Products & Chemicals | 68.38 Bn | 66.28 Bn | 1.04 Bn | -88.80 Mn |
| 5 | LyondellBasell Industries | 42.93 Bn | 32.55 Bn | 2.04 Bn | - |
| 6 | Nutrien | 33.61 Bn | 30.47 Bn | 3.25 Bn | -10.00 Mn |
| 7 | Ppg Industries | 24.59 Bn | 17.39 Bn | 1.81 Bn | -66.00 Mn |
| 8 | International Flavors & Fragrances | 24.03 Bn | 21.72 Bn | 853.00 Mn | 3.00 Mn |
| 9 | Dow | 23.60 Bn | 9.04 Bn | 1.38 Bn | 2.00 Mn |
| 10 | Qnity Electronics | 22.98 Bn | 20.41 Bn | 666.00 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 3.00 Mn |
| Mar 31, 2026 | 198.00 Mn |
| Dec 31, 2025 | 36.00 Mn |
| Jun 30, 2025 | 2.71 Bn |
| Dec 31, 2024 | -1.00 Mn |
| Sep 30, 2024 | 28.00 Mn |
| Jun 30, 2024 | 811.00 Mn |
| Mar 31, 2024 | 37.00 Mn |
| Dec 31, 2023 | 44.00 Mn |
| Sep 30, 2023 | 185.00 Mn |
| Jun 30, 2023 | 820.00 Mn |
| Mar 31, 2023 | 1.00 Mn |
| Dec 31, 2022 | 22.00 Mn |
| Sep 30, 2022 | 1.17 Bn |
| Jun 30, 2022 | -123.00 Mn |
| Mar 31, 2022 | -11.00 Mn |
| Dec 31, 2021 | 193.00 Mn |
| Jun 30, 2021 | -400.00 Mn |
| Mar 31, 2021 | 207.00 Mn |
| Dec 31, 2019 | 65,000.00 |
API Access
International Flavors & Fragrances 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=IFF&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "net-of-acquisitions-and-divestments", "ticker": "IFF", "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=IFF&period=max&api_key=YOUR_API_KEY");
const data = await res.json();