Neurocrine Biosciences (NBIX) Accumulated Expenses (2010 - 2017)
Neurocrine Biosciences' Accumulated Expenses came in at $18.4 million for Q1 2017, up 7.5% from $17.13 million a year earlier but down 12.8% from the prior quarter.
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Analysis
Neurocrine Biosciences (NBIX) Accumulated Expenses (2010 - 2017) Analysis & Trends
At the end of FY2016, Neurocrine Biosciences' Accumulated Expenses was $21.1 million, up 10.8% from FY2015.
- Accumulated Expenses has increased in each of the last three years, with a five-year compound annual growth rate of 20.1% (FY2011 to FY2016).
- Going back by year, Accumulated Expenses was $19.03 million in FY2015 (+65.4%), $11.51 million in FY2014 (+44.7%), $7.96 million in FY2013 (-1.7%) and $8.09 million in FY2012 (-4.2%).
- The five-year range for quarterly Accumulated Expenses is $6.11 million (Q1 2014) to $21.1 million (Q4 2016).
- Year-over-year, Accumulated Expenses has increased for 11 consecutive quarters, with growth averaging 48.9% over the last eight quarters.
- The fastest year-over-year change in Accumulated Expenses over five years came in Q1 2016 (growth of 72.3%), and the weakest in Q2 2014 (a decline of 9.1%).
- Business Quant data shows NBIX's Accumulated Expenses at $21.1 million (Q4 2016), $20.75 million (Q3 2016) and $21.02 million (Q2 2016) in the three quarters before Q1 2017.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Johnson & Johnson | 638.12 Bn | 556.64 Bn | 17.26 Bn |
| 2 | AbbVie | 462.60 Bn | 435.75 Bn | 12.70 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 |
| 6 | Amgen | 227.87 Bn | 183.27 Bn | 7.24 Bn |
| 7 | Gilead Sciences | 184.97 Bn | 159.08 Bn | 6.22 Bn |
| 8 | Pfizer | 162.61 Bn | 109.56 Bn | 10.94 Bn |
| 9 | Vertex Pharmaceuticals | 132.45 Bn | 104.46 Bn | 2.84 Bn |
| 10 | Neurocrine Biosciences | 14.41 Bn | 10.11 Bn | 935.80 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Mar 31, 2017 | 18.40 Mn |
| Dec 31, 2016 | 21.10 Mn |
| Sep 30, 2016 | 20.75 Mn |
| Jun 30, 2016 | 21.02 Mn |
| Mar 31, 2016 | 17.13 Mn |
| Dec 31, 2015 | 19.03 Mn |
| Sep 30, 2015 | 14.51 Mn |
| Jun 30, 2015 | 12.39 Mn |
| Mar 31, 2015 | 9.94 Mn |
| Dec 31, 2014 | 11.51 Mn |
| Sep 30, 2014 | 9.31 Mn |
| Jun 30, 2014 | 7.44 Mn |
| Mar 31, 2014 | 6.11 Mn |
| Dec 31, 2013 | 7.96 Mn |
| Sep 30, 2013 | 7.88 Mn |
| Jun 30, 2013 | 8.19 Mn |
| Mar 31, 2013 | 6.58 Mn |
| Dec 31, 2012 | 8.09 Mn |
| Sep 30, 2012 | 8.13 Mn |
| Jun 30, 2012 | 6.94 Mn |
API Access
Neurocrine Biosciences Accumulated 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=accumulated-expenses&ticker=NBIX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "NBIX", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=NBIX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();