Alcoa Tax Assets Trend

AA -- USA Stock  

USD 39.71  1.11  2.88%

This module enables investors to look at Alcoa 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 Cost of Revenue of 10.6 B, Gross Profit of 2.6 B or Interest Expense of 317.6 M, but also many exotic indicators such as Interest Coverage of 0.9366, Long Term Debt to Equity of 0.0258 or PPandE Turnover of 1.272. This module is a perfect complement to use when analyzing Alcoa Valuation or Volatility. It can also complement various Alcoa Technical models. Check also analysis of Alcoa Correlation with competitors.
Showing smoothed Tax Assets of Alcoa Corporation with missing and latest data points interpolated. A component of Total Assets representing tax assets and receivables.
Tax Assets10 Years Trend
Decreasing
Slightly volatile
 Tax Assets 
      Timeline 

Alcoa Regression Statistics

Arithmetic Mean 914,995,098
Geometric Mean 886,107,868
Coefficient Of Variation 24.40
Mean Deviation 200,006,536
Median 1,065,000,000
Standard Deviation 223,227,996
Range 476,000,000
R Value(0.80)
R Squared 0.63
Significance 0.001968
Slope(49,261,004)

Alcoa Tax Assets Over Time

2016-12-31  589,000,000 
2017-12-31  589,000,000 
2018-12-31  692,941,176 

Other Fundumenentals of Alcoa

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Alcoa Fundamental Drivers

Alcoa Corporation Fundamental Market Drivers

Short Percent Of Float2.83%
Forward Price Earnings9.86
Shares Short Prior Month8.47M
Average Daily Volume Last 10 Day5.26M
Average Daily Volume In Three Month4.63M
Date Short InterestSeptember 28, 2018
Fifty Day Average40.78
Two Hundred Day Average46.08

Alcoa Upcoming Events

Alcoa Upcoming Company Events

Upcoming Quarterly ReportApril 10, 2017
Next Earnings ReportJuly 10, 2017
Check also analysis of Alcoa Correlation with competitors. Please also try Headlines Timeline module to stay connected to all market stories and filter out noise. drill down to analyze hype elasticity.
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