Axe Compute (AGPU) Operating Margin (2011 - 2019)
Axe Compute's Operating Margin was -844.57% in Q1 2019, down 482.17 percentage points from -362.39% a year earlier but up 1166.64 percentage points from the prior quarter.
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Analysis
Axe Compute (AGPU) Operating Margin (2011 - 2019) Analysis & Trends
On a trailing twelve-month basis, Axe Compute's Operating Margin was -719.17% through Mar 31, 2019, up 63.54 percentage points year-over-year; for FY2018, it was -486.34%, up 360.70 percentage points from FY2017.
- Operating Margin shows a five-year change of -311.49 percentage points (FY2013 to FY2018).
- In earlier years, Operating Margin was -847.04% in FY2017 (-653.56 pp), -193.48% in FY2016 (-117.64 pp), -75.85% in FY2015 (-33.12 pp) and -42.73% in FY2014 (+132.13 pp).
- Quarterly Operating Margin has moved between -2413.87% (Q4 2017) and 22.47% (Q1 2015) over five years.
- Compared with a year earlier, Operating Margin was higher in four of the last eight quarters, with an average year-over-year change of -318.23 percentage points.
- The best year-over-year quarter for Operating Margin over five years was Q4 2018 (a gain of 402.67 percentage points); the worst was Q4 2017 (a drop of 2325.76 percentage points).
- Per Business Quant data, AGPU's Operating Margin in the three quarters before Q1 2019 was -2011.20% (Q4 2018), -144.58% (Q3 2018) and -36.06% (Q2 2018).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Operating Margin (Qtr) |
|---|---|---|---|---|---|
| 1 | Microsoft | 3,781.98 Bn | 3,705.13 Bn | 60.48 Bn | 45.11% |
| 2 | International Business Machines | 207.92 Bn | 158.82 Bn | 9.91 Bn | 15.24% |
| 3 | Cloudflare | 114.07 Bn | 97.60 Bn | 499.52 Mn | -29.55% |
| 4 | Equinix | 99.76 Bn | 88.32 Bn | 1.40 Bn | 25.33% |
| 5 | Nebius | 58.67 Bn | 32.10 Bn | 448.70 Mn | -30.21% |
| 6 | CoreWeave | 46.87 Bn | 33.97 Bn | 1.70 Bn | -1.90% |
| 7 | Verisign | 25.50 Bn | 22.71 Bn | 384.60 Mn | 68.18% |
| 8 | Nutanix | 18.59 Bn | 10.27 Bn | 651.35 Mn | 9.24% |
| 9 | Akamai Technologies | 15.65 Bn | 9.06 Bn | 613.75 Mn | 7.30% |
| 10 | Axe Compute | 239.18 Mn | 199.38 Mn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Mar 31, 2019 | -844.57% |
| Dec 31, 2018 | -2,011.20% |
| Sep 30, 2018 | -144.58% |
| Jun 30, 2018 | -36.06% |
| Mar 31, 2018 | -362.39% |
| Dec 31, 2017 | -2,413.87% |
| Sep 30, 2017 | -45.04% |
| Jun 30, 2017 | -91.46% |
| Mar 31, 2017 | -35.58% |
| Dec 31, 2016 | -88.12% |
| Sep 30, 2016 | -137.24% |
| Jun 30, 2016 | -229.66% |
| Mar 31, 2016 | -391.46% |
| Dec 31, 2015 | -214.24% |
| Sep 30, 2015 | -159.43% |
| Jun 30, 2015 | -0.37% |
| Mar 31, 2015 | 22.47% |
| Dec 31, 2014 | -113.50% |
| Sep 30, 2014 | 19.98% |
| Jun 30, 2014 | -22.51% |
API Access
Axe Compute Operating Margin 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=operating-margin&ticker=AGPU&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-margin", "ticker": "AGPU", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-margin&ticker=AGPU&period=max&api_key=YOUR_API_KEY");
const data = await res.json();