Correlation Between Mfs Blended and Massachusetts Investors
Can any of the company-specific risk be diversified away by investing in both Mfs Blended and Massachusetts Investors 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 Blended and Massachusetts Investors into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mfs Blended Research and Massachusetts Investors Trust, you can compare the effects of market volatilities on Mfs Blended and Massachusetts Investors 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 Blended with a short position of Massachusetts Investors. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mfs Blended and Massachusetts Investors.
Diversification Opportunities for Mfs Blended and Massachusetts Investors
-0.56 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Mfs and Massachusetts is -0.56. Overlapping area represents the amount of risk that can be diversified away by holding Mfs Blended Research and Massachusetts Investors Trust in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Massachusetts Investors and Mfs Blended 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 Blended Research are associated (or correlated) with Massachusetts Investors. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Massachusetts Investors has no effect on the direction of Mfs Blended i.e., Mfs Blended and Massachusetts Investors go up and down completely randomly.
Pair Corralation between Mfs Blended and Massachusetts Investors
Assuming the 90 days horizon Mfs Blended Research is expected to generate 0.55 times more return on investment than Massachusetts Investors. However, Mfs Blended Research is 1.81 times less risky than Massachusetts Investors. It trades about -0.04 of its potential returns per unit of risk. Massachusetts Investors Trust is currently generating about -0.1 per unit of risk. If you would invest 1,408 in Mfs Blended Research on September 21, 2024 and sell it today you would lose (35.00) from holding Mfs Blended Research or give up 2.49% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 98.44% |
Values | Daily Returns |
Mfs Blended Research vs. Massachusetts Investors Trust
Performance |
Timeline |
Mfs Blended Research |
Massachusetts Investors |
Mfs Blended and Massachusetts Investors Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mfs Blended and Massachusetts Investors
The main advantage of trading using opposite Mfs Blended and Massachusetts Investors positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mfs Blended position performs unexpectedly, Massachusetts Investors 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 Massachusetts Investors will offset losses from the drop in Massachusetts Investors' long position.Mfs Blended vs. Mfs Prudent Investor | Mfs Blended vs. Mfs Prudent Investor | Mfs Blended vs. Mfs Prudent Investor | Mfs Blended vs. Mfs Prudent Investor |
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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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