Facebook Calculated Tax Rate Trend

FB -- USA Stock  

USD 153.18  0.87  0.56%

This module enables investors to look at Facebook 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 13.8 B, Cost of Revenue of 4.9 B or Earning Before Interest and Taxes EBIT of 17.4 B, but also many exotic indicators such as Interest Coverage of 89.1574, Long Term Debt to Equity of 0.0028 or Calculated Tax Rate of 21.5839. This module is a perfect complement to use when analyzing Facebook Valuation or Volatility. It can also complement various Facebook Technical models. Additionally see analysis of Facebook Correlation with competitors.
Showing smoothed Calculated Tax Rate of Facebook with missing and latest data points interpolated.
Calculated Tax Rate10 Years Trend
Increasing
Stable
 Calculated Tax Rate 
      Timeline 

Facebook Regression Statistics

Arithmetic Mean 32.37
Geometric Mean 25.93
Coefficient Of Variation 69.69
Mean Deviation 17.01
Median 39.88
Standard Deviation 22.56
Sample Variance 508.81
Range 79.43
R Value 0.15
Mean Square Error 547.82
R Squared 0.021198
Significance 0.65
Slope 0.91
Total Sum of Squares 5,597

Facebook Calculated Tax Rate Over Time

2016-12-31  18.38 
2017-12-31  22.63 
2018-12-31  21.58 

Other Fundumenentals of Facebook

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Facebook Fundamental Drivers

Facebook Fundamental Market Drivers

Short Percent Of Float1.12%
Forward Price Earnings18.67
Shares Short Prior Month25.29M
Average Daily Volume Last 10 Day22.96M
Average Daily Volume In Three Month28.63M
Date Short InterestSeptember 28, 2018
Fifty Day Average162.21
Two Hundred Day Average178.51

Facebook Upcoming Events

Facebook Upcoming Company Events

Upcoming Quarterly ReportMay 2, 2018
Next Earnings ReportJuly 25, 2018
Additionally see analysis of Facebook Correlation with competitors. Please also try Watchlist Optimization module to optimize watchlists to build efficient portfolio or rebalance existing positions based on mean-variance optimization algorithm.
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