Citigroup Debt to Equity Ratio Trend

C -- USA Stock  

USD 74.15  0.31  0.42%

This module enables investors to look at Citigroup 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 17 B or Cost of Revenue of 7.8 B, but also many exotic indicators such as Calculated Tax Rate of 31.5646 or Cash and Equivalents Turnover of 0.6114. This module is a perfect complement to use when analyzing Citigroup Valuation or Volatility. It can also complement various Citigroup Technical models. Check also analysis of Citigroup Correlation with competitors.
Showing smoothed Debt to Equity Ratio of Citigroup with missing and latest data points interpolated. Measures the ratio between Total Liabilities and Shareholders Equity.
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0.91 %

          10 Years Trend
Decreasing
Slightly volatile
 Debt to Equity Ratio 
      Timeline 

Citigroup Regression Statistics

Arithmetic Mean 8.76
Geometric Mean 7.57
Coefficient Of Variation 39.76
Mean Deviation 2.50
Median 8.85
Standard Deviation 3.48
Sample Variance 12.13
Range 13.75
R Value(0.93)
Mean Square Error 1.76
R Squared 0.87
Significance 0.00001032
Slope(0.90)
Total Sum of Squares 133.43

Citigroup Debt to Equity Ratio Over Time

2016-12-31  6.96 
2017-12-31  6.96 
2018-12-31  0.91 

Other Fundumenentals of Citigroup

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Citigroup Fundamental Drivers

Citigroup Fundamental Market Drivers

Short Percent Of Float0.64%
Forward Price Earnings9.83
Shares Short Prior Month19.54M
Average Daily Volume Last 10 Day15.55M
Average Daily Volume In Three Month14.71M
Date Short InterestAugust 31, 2018
Fifty Day Average71.05
Two Hundred Day Average69.88

Citigroup Upcoming Events

Citigroup Upcoming Company Events

Upcoming Quarterly ReportJanuary 16, 2018
Next Earnings ReportApril 12, 2018
Check also analysis of Citigroup Correlation with competitors. Please also try Pattern Recognition module to use different pattern recognition models to time the market across multiple global exchanges.
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