Macys Return on Average Equity Trend

M -- USA Stock  

USD 30.80  0.19  0.62%

This module enables investors to look at Macys 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 Direct Expenses of 16.2 B or Consolidated Income of 88.2 M, but also many exotic indicators such as Interest Coverage of 4.0509 or Long Term Debt to Equity of 1.3427. This module is a perfect complement to use when analyzing Macys Valuation or Volatility. It can also complement various Macys Technical models. Please see also analysis of Macys Correlation with competitors.
Showing smoothed Return on Average Equity of Macys with missing and latest data points interpolated. Return on equity measures a corporation's profitability by calculating the amount of Net Income Common Stock returned as a percentage of Average Equity.


          10 Years Trend
Very volatile
 Return on Average Equity 

Macys Regression Statistics

Arithmetic Mean 0.15
Geometric Mean 0.13
Coefficient Of Variation 59.99
Mean Deviation 0.06
Median 0.11
Standard Deviation 0.09
Sample Variance 0.007742
Range 0.23
R Value 0.018755
Mean Square Error 0.008513
R Squared 0.00035176
Significance 0.95
Slope 0.00045769
Total Sum of Squares 0.09

Macys Return on Average Equity Over Time

2007  0.33 
2008  0.11 
2018  0.34 

Other Fundumenentals of Macys

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Macys Fundamental Drivers

Macys Fundamental Market Drivers

Short Percent Of Float14.48%
Forward Price Earnings8.48
Shares Short Prior Month44M
Average Daily Volume Last 10 Day5.99M
Average Daily Volume In Three Month7.82M
Date Short InterestNovember 15, 2018
Fifty Day Average33.99
Two Hundred Day Average36.04

Macys Upcoming Events

Macys Upcoming Company Events

Upcoming Quarterly ReportMay 10, 2017
Next Earnings ReportAugust 10, 2017
Please see also analysis of Macys Correlation with competitors. Please also try Pattern Recognition module to use different pattern recognition models to time the market across multiple global exchanges.