Becton Dickinson (BDX) Payout Ratio (2009 - 2017)
Becton Dickinson's (BDX) Payout Ratio came in at 0.71 for FY2025 (year ended Sep 30, 2025), up 10.5% from 0.65 in FY2024.
Analysis
Becton Dickinson (BDX) Payout Ratio (2009 - 2017) Analysis & Trends
Since FY2009, Becton Dickinson has reported Payout Ratio for 17 fiscal years.
- Annual Payout Ratio has run from a low of 0.52 in FY2021 to a high of 0.78 in FY2023 over five years.
- Business Quant data shows BDX's Payout Ratio at 0.65 in FY2024 (-17.5%), 0.78 in FY2023 (+22.1%), 0.64 in FY2022 (+22.4%) and 0.52 in FY2021 (-60.9%).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 250.84 Bn | 229.99 Bn | 4.88 Bn |
| 2 | Abbott Laboratories | 174.73 Bn | 145.82 Bn | 7.27 Bn |
| 3 | Danaher | 159.85 Bn | 143.67 Bn | 3.61 Bn |
| 4 | Intuitive Surgical | 146.79 Bn | 126.35 Bn | 1.96 Bn |
| 5 | Medtronic | 114.54 Bn | 80.41 Bn | 6.34 Bn |
| 6 | Stryker | 105.67 Bn | 91.79 Bn | 4.50 Bn |
| 7 | Boston Scientific | 63.93 Bn | 58.94 Bn | 3.85 Bn |
| 8 | Becton Dickinson | 50.12 Bn | 47.27 Bn | 2.32 Bn |
| 9 | Edwards Lifesciences | 50.06 Bn | 34.17 Bn | 1.35 Bn |
| 10 | Agilent Technologies | 49.40 Bn | 42.29 Bn | 1.04 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2017 | 0.66 |
| Jun 30, 2017 | 0.82 |
| Mar 31, 2017 | 0.45 |
| Dec 31, 2016 | 0.44 |
| Sep 30, 2016 | 0.58 |
| Jun 30, 2016 | 0.48 |
| Mar 31, 2016 | 0.66 |
| Dec 31, 2015 | 0.74 |
| Sep 30, 2015 | 0.70 |
| Jun 30, 2015 | 0.57 |
| Mar 31, 2015 | 0.41 |
| Dec 31, 2014 | 0.37 |
| Sep 30, 2014 | 0.36 |
| Jun 30, 2014 | 0.42 |
| Mar 31, 2014 | 0.43 |
| Dec 31, 2013 | 0.42 |
| Sep 30, 2013 | 0.30 |
| Jun 30, 2013 | 0.25 |
| Mar 31, 2013 | 0.25 |
| Dec 31, 2012 | 0.24 |
API Access
Becton Dickinson Payout Ratio 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=payout-ratio&ticker=BDX&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "payout-ratio", "ticker": "BDX", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=payout-ratio&ticker=BDX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();