Ford Motor Total Assets Per Share Trend

F -- USA Stock  

USD 8.64  0.12  1.41%

This module enables investors to look at Ford Motor 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 135.7 B or Consolidated Income of 6.4 B, but also many exotic indicators such as Interest Coverage of 7.3801 or Long Term Debt to Equity of 3.2322. This module is a perfect complement to use when analyzing Ford Motor Valuation or Volatility. It can also complement various Ford Motor Technical models. Additionally see analysis of Ford Motor Correlation with competitors.
Showing smoothed Total Assets Per Share of Ford Motor Company with missing and latest data points interpolated.
Total Assets Per Share10 Years Trend
Decreasing
Stable
 Total Assets Per Share 
      Timeline 

Ford Motor Regression Statistics

Arithmetic Mean 59.96
Geometric Mean 58.23
Coefficient Of Variation 26.95
Mean Deviation 12.15
Median 56.66
Standard Deviation 16.16
Sample Variance 261.11
Range 47.57
R Value(0.27)
Mean Square Error 266.05
R Squared 0.07
Significance 0.39
Slope(1.22)
Total Sum of Squares 2,872

Ford Motor Total Assets Per Share Over Time

2016  59.87 
2017  64.88 
2018  65.66 

Other Fundumenentals of Ford Motor

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Ford Motor Fundamental Drivers

Ford Motor Company Fundamental Market Drivers

Short Percent Of Float2.97%
Forward Price Earnings6.78
Shares Short Prior Month117.87M
Average Daily Volume Last 10 Day37.73M
Average Daily Volume In Three Month46.9M
Date Short InterestOctober 31, 2018
Fifty Day Average9.20
Two Hundred Day Average10.07

Ford Motor Upcoming Events

Ford Motor Upcoming Company Events

Upcoming Quarterly ReportJuly 25, 2018
Next Earnings ReportOctober 25, 2018
Additionally see analysis of Ford Motor Correlation with competitors. Please also try Correlation Analysis module to reduce portfolio risk simply by holding instruments which are not perfectly correlated.
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