Correlation Between Ford and Interface
Can any of the company-specific risk be diversified away by investing in both Ford and Interface at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Ford and Interface into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ford Motor and Interface, you can compare the effects of market volatilities on Ford and Interface 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 with a short position of Interface. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ford and Interface.
Diversification Opportunities for Ford and Interface
Poor diversification
The 3 months correlation between Ford and Interface is 0.6. Overlapping area represents the amount of risk that can be diversified away by holding Ford Motor and Interface in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Interface and Ford 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 are associated (or correlated) with Interface. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Interface has no effect on the direction of Ford i.e., Ford and Interface go up and down completely randomly.
Pair Corralation between Ford and Interface
Given the investment horizon of 90 days Ford is expected to generate 1.44 times less return on investment than Interface. But when comparing it to its historical volatility, Ford Motor is 2.18 times less risky than Interface. It trades about 0.15 of its potential returns per unit of risk. Interface is currently generating about 0.1 of returns per unit of risk over similar time horizon. If you would invest 1,874 in Interface on April 25, 2025 and sell it today you would earn a total of 193.00 from holding Interface or generate 10.3% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Ford Motor vs. Interface
Performance |
Timeline |
Ford Motor |
Interface |
Ford and Interface Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Ford and Interface
The main advantage of trading using opposite Ford and Interface positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ford position performs unexpectedly, Interface can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Interface will offset losses from the drop in Interface's long position.The idea behind Ford Motor and Interface pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.Interface vs. Gibraltar Industries | Interface vs. Janus International Group | Interface vs. Quanex Building Products | Interface vs. Jeld Wen Holding |
Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Portfolio Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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