- Companies in United States
- Peer Analysis
This module allows you to analyze existing cross correlation between Ford Motor Company and S&P 500. You can compare the effects of market volatilities on Ford Motor and SP 500 and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in Ford Motor with a short position of SP 500. See also your portfolio center. Please also check ongoing floating volatility patterns of Ford Motor and SP 500.
|Horizon||30 Days Login to change|
Predicted Return Density
Ford Motor Company vs. S&P 500
Taking into account the 30 trading days horizon, Ford Motor is expected to generate 16.61 times less return on investment than SP 500. In addition to that, Ford Motor is 2.44 times more volatile than S&P 500. It trades about 0.01 of its total potential returns per unit of risk. S&P 500 is currently generating about 0.23 per unit of volatility. If you would invest 267,071 in S&P 500 on February 17, 2019 and sell it today you would earn a total of 16,223 from holding S&P 500 or generate 6.07% return on investment over 30 days.
Pair Corralation between Ford Motor and SP 500
|Time Period||2 Months [change]|
Diversification Opportunities for Ford Motor and SP 500
Overlapping area represents the amount of risk that can be diversified away by holding Ford Motor Company and S&P 500 in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on SP 500 and Ford Motor is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on Ford Motor Company are associated (or correlated) with SP 500. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SP 500 has no effect on the direction of Ford Motor i.e. Ford Motor and SP 500 go up and down completely randomly.