Gartner Gross Profit Trend

IT -- USA Stock  

USD 139.63  0.50  0.36%

This module enables investors to look at Gartner various fundamental indicators over time in order to gain insight into the company future performance. Macroaxis historical fundamental analysis tools allow evaluation of not only typical financial statement drivers such as Consolidated Income of 194.3 M, Cost of Revenue of 939.3 M or Earning Before Interest and Taxes EBIT of 321.4 M, but also many exotic indicators such as Interest Coverage of 13.688, Long Term Debt to Equity of 12.8394 or Calculated Tax Rate of 35.9804. This module is a perfect complement to use when analyzing Gartner Valuation or Volatility. It can also complement various Gartner Technical models. Please also check analysis of Gartner Correlation with competitors.
Showing smoothed Gross Profit of Gartner with missing and latest data points interpolated. Gross profit is a required income statement account that reflects total revenue of Gartner minus its cost of goods sold. It is profit before Gartner operating expenses, interest payments and taxes. Gross profit is also known as gross margin. Aggregate revenue Revenues less cost of revenue Cost of Revenue directly attributable to the revenue generation activity.

1.99 B

          10 Years Trend
Slightly volatile
 Gross Profit 

Regression Statistics

Arithmetic Mean  1,084,958,167
Geometric Mean  1,007,295,170
Coefficient Of Variation  40.22
Mean Deviation  351,746,861
Median  1,070,729,000
Standard Deviation  436,362,515
Range  1,477,587,000
R Value  0.97
R Squared  0.94
Significance  0.00000023
Slope  117,230,035

Gartner Gross Profit Over Time

2016-12-31  1,498,892,000 
2017-12-31  1,498,892,000 
2018-12-31  1,990,000,000 

Other Fundumenentals

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Gartner Upcoming Company Events

Upcoming Quarterly ReportMay 4, 2017
Next Earnings ReportAugust 3, 2017
Please also check analysis of Gartner Correlation with competitors. Please also try Idea Optimizer module to use advanced portfolio builder with pre-computed micro ideas to build optimal portfolio .