Correlation Between MFS Investment and Bny Mellon
Can any of the company-specific risk be diversified away by investing in both MFS Investment and Bny Mellon 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 Investment and Bny Mellon into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between MFS Investment Grade and Bny Mellon Municipal, you can compare the effects of market volatilities on MFS Investment and Bny Mellon 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 Investment with a short position of Bny Mellon. Check out your portfolio center. Please also check ongoing floating volatility patterns of MFS Investment and Bny Mellon.
Diversification Opportunities for MFS Investment and Bny Mellon
0.71 | Correlation Coefficient |
Poor diversification
The 3 months correlation between MFS and Bny is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding MFS Investment Grade and Bny Mellon Municipal in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bny Mellon Municipal and MFS Investment 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 Investment Grade are associated (or correlated) with Bny Mellon. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bny Mellon Municipal has no effect on the direction of MFS Investment i.e., MFS Investment and Bny Mellon go up and down completely randomly.
Pair Corralation between MFS Investment and Bny Mellon
Considering the 90-day investment horizon MFS Investment is expected to generate 1.54 times less return on investment than Bny Mellon. But when comparing it to its historical volatility, MFS Investment Grade is 1.11 times less risky than Bny Mellon. It trades about 0.19 of its potential returns per unit of risk. Bny Mellon Municipal is currently generating about 0.26 of returns per unit of risk over similar time horizon. If you would invest 1,064 in Bny Mellon Municipal on September 2, 2024 and sell it today you would earn a total of 39.00 from holding Bny Mellon Municipal or generate 3.67% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
MFS Investment Grade vs. Bny Mellon Municipal
Performance |
Timeline |
MFS Investment Grade |
Bny Mellon Municipal |
MFS Investment and Bny Mellon Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with MFS Investment and Bny Mellon
The main advantage of trading using opposite MFS Investment and Bny Mellon positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if MFS Investment position performs unexpectedly, Bny Mellon 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 Bny Mellon will offset losses from the drop in Bny Mellon's long position.MFS Investment vs. Invesco High Income | MFS Investment vs. Eaton Vance National | MFS Investment vs. Nuveen California Select | MFS Investment vs. Federated Premier Municipal |
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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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