Baxter International (BAX) Non Operating Interest Expenses (2009 - 2019)
Baxter International's Non Operating Interest Expenses was $28 million in Q2 2019, up 16.7% from $24 million a year earlier and up 12.0% from the prior quarter.
Powered by 
Analysis
Baxter International (BAX) Non Operating Interest Expenses (2009 - 2019) Analysis & Trends
On a trailing twelve-month basis, Baxter International's Non Operating Interest Expenses was $100 million through Jun 30, 2019, up 9.9% year-over-year; for FY2018, it was $93 million, up 9.4% from FY2017.
- Non Operating Interest Expenses shows a five-year compound annual growth rate of -9.7% (FY2013 to FY2018).
- In earlier years, Non Operating Interest Expenses was $85 million in FY2017 (-4.5%), $89 million in FY2016 (-39.0%), $146 million in FY2015 (-12.6%) and $167 million in FY2014 (+7.7%).
- The Q2 2019 figure marks the highest quarterly Non Operating Interest Expenses since Q1 2016.
- Compared with a year earlier, Non Operating Interest Expenses was higher in seven of the last eight quarters, with growth averaging 11.1%.
- The best year-over-year quarter for Non Operating Interest Expenses over five years was Q2 2017 (growth of 31.3%); the worst was Q2 2016 (a decline of 55.6%).
- Per Business Quant data, BAX's Non Operating Interest Expenses in the three quarters before Q2 2019 was $25 million (Q1 2019), $23 million (Q4 2018) and $24 million (Q3 2018).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Non Operating Interest Expenses (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 249.71 Bn | 228.86 Bn | 4.88 Bn | 401.00 Mn |
| 2 | Abbott Laboratories | 171.00 Bn | 142.08 Bn | 7.27 Bn | 351.00 Mn |
| 3 | Danaher | 155.79 Bn | 139.61 Bn | 3.61 Bn | 107.00 Mn |
| 4 | Intuitive Surgical | 143.91 Bn | 123.46 Bn | 1.96 Bn | - |
| 5 | Medtronic | 110.42 Bn | 76.29 Bn | 6.34 Bn | 186.00 Mn |
| 6 | Stryker | 105.71 Bn | 91.82 Bn | 4.50 Bn | 141.00 Mn |
| 7 | Boston Scientific | 63.26 Bn | 58.27 Bn | 3.85 Bn | 96.00 Mn |
| 8 | Edwards Lifesciences | 49.80 Bn | 33.91 Bn | 1.35 Bn | - |
| 9 | Becton Dickinson | 48.78 Bn | 45.93 Bn | 2.32 Bn | 132.00 Mn |
| 10 | Baxter International | 12.41 Bn | 4.52 Bn | 1.03 Bn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2019 | 28.00 Mn |
| Mar 31, 2019 | 25.00 Mn |
| Dec 31, 2018 | 23.00 Mn |
| Sep 30, 2018 | 24.00 Mn |
| Jun 30, 2018 | 24.00 Mn |
| Mar 31, 2018 | 22.00 Mn |
| Dec 31, 2017 | 23.00 Mn |
| Sep 30, 2017 | 22.00 Mn |
| Jun 30, 2017 | 21.00 Mn |
| Mar 31, 2017 | 20.00 Mn |
| Dec 31, 2016 | 20.00 Mn |
| Sep 30, 2016 | 20.00 Mn |
| Jun 30, 2016 | 16.00 Mn |
| Mar 31, 2016 | 33.00 Mn |
| Dec 31, 2015 | 37.00 Mn |
| Sep 30, 2015 | 38.00 Mn |
| Jun 30, 2015 | 36.00 Mn |
| Mar 31, 2015 | 35.00 Mn |
| Dec 31, 2014 | 36.00 Mn |
| Sep 30, 2014 | 36.00 Mn |
API Access
Baxter International Non Operating Interest 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=non-operating-interest-expenses&ticker=BAX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "non-operating-interest-expenses", "ticker": "BAX", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=non-operating-interest-expenses&ticker=BAX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();