Ford Motor Trade and Non Trade Receivables Trend

F -- USA Stock  

USD 8.50  0.14  1.62%

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 Trade and Non Trade Receivables of Ford Motor Company with missing and latest data points interpolated. A component of Total Assets representing trade and non-trade receivables.
Trade and Non Trade Receivables10 Years Trend
Very volatile
 Trade and Non Trade Receivables 

Ford Motor Regression Statistics

Arithmetic Mean 102,272,942,982
Geometric Mean 99,416,291,422
Coefficient Of Variation 27.50
Mean Deviation 19,202,923,977
Median 99,158,000,000
Standard Deviation 28,127,074,337
Range 100,479,000,000
R Value(0.07)
R Squared 0.004256
Significance 0.84

Ford Motor Trade and Non Trade Receivables Over Time

2016  107,292,000,000 
2017  118,991,000,000 
2018  119,096,315,789 

Other Fundumenentals of Ford Motor

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Ford Motor Fundamental Drivers

Ford Motor Company Fundamental Market Drivers

Short Percent Of Float2.99%
Forward Price Earnings6.39
Shares Short Prior Month130.63M
Average Daily Volume Last 10 Day44.94M
Average Daily Volume In Three Month48.05M
Date Short InterestNovember 15, 2018
Fifty Day Average9.23
Two Hundred Day Average9.97

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 Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.