Arbutus Biopharma (ABUS) Change in Taxes (2013 - 2019)
Arbutus Biopharma's Change in Taxes was -$98,000 in Q1 2019, compared with $2,000 a year earlier.
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Analysis
Arbutus Biopharma (ABUS) Change in Taxes (2013 - 2019) Analysis & Trends
On a trailing twelve-month basis, Arbutus Biopharma's Change in Taxes was -$51,000 through Mar 31, 2019; for FY2018, it was $49,000, up 4.3% from FY2017.
- Change in Taxes shows a five-year compound annual growth rate of 9.6% (FY2013 to FY2018).
- In earlier years, Change in Taxes was $47,000 in FY2017 (unchanged), $47,000 in FY2016 (-75.0%), $188,000 in FY2015 (+261.5%) and $52,000 in FY2014 (+67.7%).
- The Q1 2019 figure marks the lowest quarterly Change in Taxes since Q2 2017.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Taxes (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 638.12 Bn | 556.64 Bn | 17.26 Bn | - |
| 2 | AbbVie | 462.60 Bn | 435.75 Bn | 12.70 Bn | -2.22 Bn |
| 3 | Merck | 358.70 Bn | 313.13 Bn | 12.21 Bn | - |
| 4 | Novartis Ag | 272.16 Bn | 228.03 Bn | 11.24 Bn | - |
| 5 | Astrazeneca | 250.36 Bn | 223.92 Bn | 12.86 Bn | -1.53 Bn |
| 6 | Amgen | 227.87 Bn | 183.27 Bn | 7.24 Bn | -131.00 Mn |
| 7 | Gilead Sciences | 184.97 Bn | 159.08 Bn | 6.22 Bn | 171.00 Mn |
| 8 | Pfizer | 162.61 Bn | 109.56 Bn | 10.94 Bn | - |
| 9 | Vertex Pharmaceuticals | 132.45 Bn | 104.46 Bn | 2.84 Bn | - |
| 10 | Arbutus Biopharma | 944.69 Mn | 571.67 Mn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Mar 31, 2019 | -98,000.00 |
| Dec 31, 2018 | 47,000.00 |
| Mar 31, 2018 | 2,000.00 |
| Dec 31, 2017 | 180,000.00 |
| Jun 30, 2017 | -294,000.00 |
| Mar 31, 2017 | 15,000.00 |
| Dec 31, 2016 | 145,000.00 |
| Jun 30, 2016 | -98,000.00 |
| Dec 31, 2015 | 188,000.00 |
| Dec 31, 2013 | 41,000.00 |
| Jun 30, 2013 | -10,000.00 |
API Access
Arbutus Biopharma Change in Taxes 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=change-in-taxes&ticker=ABUS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-taxes", "ticker": "ABUS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=change-in-taxes&ticker=ABUS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();