Correlation Between Mfs Total and Mfs Research
Can any of the company-specific risk be diversified away by investing in both Mfs Total and Mfs Research 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 Mfs Total and Mfs Research into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mfs Total Return and Mfs Research International, you can compare the effects of market volatilities on Mfs Total and Mfs Research 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 Mfs Total with a short position of Mfs Research. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mfs Total and Mfs Research.
Diversification Opportunities for Mfs Total and Mfs Research
-0.52 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Mfs and Mfs is -0.52. Overlapping area represents the amount of risk that can be diversified away by holding Mfs Total Return and Mfs Research International in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mfs Research Interna and Mfs Total 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 Mfs Total Return are associated (or correlated) with Mfs Research. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mfs Research Interna has no effect on the direction of Mfs Total i.e., Mfs Total and Mfs Research go up and down completely randomly.
Pair Corralation between Mfs Total and Mfs Research
Assuming the 90 days horizon Mfs Total Return is expected to generate 0.62 times more return on investment than Mfs Research. However, Mfs Total Return is 1.61 times less risky than Mfs Research. It trades about 0.34 of its potential returns per unit of risk. Mfs Research International is currently generating about -0.05 per unit of risk. If you would invest 2,042 in Mfs Total Return on September 4, 2024 and sell it today you would earn a total of 65.00 from holding Mfs Total Return or generate 3.18% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Mfs Total Return vs. Mfs Research International
Performance |
Timeline |
Mfs Total Return |
Mfs Research Interna |
Mfs Total and Mfs Research Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mfs Total and Mfs Research
The main advantage of trading using opposite Mfs Total and Mfs Research positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mfs Total position performs unexpectedly, Mfs Research 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 Research will offset losses from the drop in Mfs Research's long position.Mfs Total vs. Mfs Prudent Investor | Mfs Total vs. Mfs Prudent Investor | Mfs Total vs. Mfs Prudent Investor | Mfs Total vs. Mfs Prudent Investor |
Mfs Research vs. Mfs Value Fund | Mfs Research vs. Mfs Total Return | Mfs Research vs. Mfs New Discovery | Mfs Research vs. Mfs Total Return |
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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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