Correlation Between Ford and Mfs New
Can any of the company-specific risk be diversified away by investing in both Ford and Mfs New 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 Mfs New into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ford Motor and Mfs New Discovery, you can compare the effects of market volatilities on Ford and Mfs New 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 Mfs New. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ford and Mfs New.
Diversification Opportunities for Ford and Mfs New
Very weak diversification
The 3 months correlation between Ford and Mfs is 0.55. Overlapping area represents the amount of risk that can be diversified away by holding Ford Motor and Mfs New Discovery in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mfs New Discovery 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 Mfs New. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mfs New Discovery has no effect on the direction of Ford i.e., Ford and Mfs New go up and down completely randomly.
Pair Corralation between Ford and Mfs New
Taking into account the 90-day investment horizon Ford Motor is expected to under-perform the Mfs New. In addition to that, Ford is 2.19 times more volatile than Mfs New Discovery. It trades about -0.02 of its total potential returns per unit of risk. Mfs New Discovery is currently generating about 0.08 per unit of volatility. If you would invest 2,910 in Mfs New Discovery on September 13, 2024 and sell it today you would earn a total of 321.00 from holding Mfs New Discovery or generate 11.03% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Ford Motor vs. Mfs New Discovery
Performance |
| Timeline |
| Ford Motor |
| Mfs New Discovery |
Ford and Mfs New Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Ford and Mfs New
The main advantage of trading using opposite Ford and Mfs New positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ford position performs unexpectedly, Mfs New 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 Mfs New will offset losses from the drop in Mfs New's long position.The idea behind Ford Motor and Mfs New Discovery 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.| Mfs New vs. Mfs Prudent Investor | Mfs New vs. Mfs Prudent Investor | Mfs New vs. Mfs Prudent Investor | Mfs New vs. Mfs Prudent Investor |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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