Correlation Between Balanced Strategy and Mfs Lifetime
Can any of the company-specific risk be diversified away by investing in both Balanced Strategy and Mfs Lifetime 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 Balanced Strategy and Mfs Lifetime into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Balanced Strategy Fund and Mfs Lifetime 2065, you can compare the effects of market volatilities on Balanced Strategy and Mfs Lifetime 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 Balanced Strategy with a short position of Mfs Lifetime. Check out your portfolio center. Please also check ongoing floating volatility patterns of Balanced Strategy and Mfs Lifetime.
Diversification Opportunities for Balanced Strategy and Mfs Lifetime
0.78 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Balanced and Mfs is 0.78. Overlapping area represents the amount of risk that can be diversified away by holding Balanced Strategy Fund and Mfs Lifetime 2065 in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mfs Lifetime 2065 and Balanced Strategy 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 Balanced Strategy Fund are associated (or correlated) with Mfs Lifetime. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mfs Lifetime 2065 has no effect on the direction of Balanced Strategy i.e., Balanced Strategy and Mfs Lifetime go up and down completely randomly.
Pair Corralation between Balanced Strategy and Mfs Lifetime
Assuming the 90 days horizon Balanced Strategy is expected to generate 1.09 times less return on investment than Mfs Lifetime. But when comparing it to its historical volatility, Balanced Strategy Fund is 1.34 times less risky than Mfs Lifetime. It trades about 0.07 of its potential returns per unit of risk. Mfs Lifetime 2065 is currently generating about 0.06 of returns per unit of risk over similar time horizon. If you would invest 821.00 in Mfs Lifetime 2065 on October 11, 2024 and sell it today you would earn a total of 170.00 from holding Mfs Lifetime 2065 or generate 20.71% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Balanced Strategy Fund vs. Mfs Lifetime 2065
Performance |
Timeline |
Balanced Strategy |
Mfs Lifetime 2065 |
Balanced Strategy and Mfs Lifetime Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Balanced Strategy and Mfs Lifetime
The main advantage of trading using opposite Balanced Strategy and Mfs Lifetime positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Balanced Strategy position performs unexpectedly, Mfs Lifetime 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 Lifetime will offset losses from the drop in Mfs Lifetime's long position.Balanced Strategy vs. Fidelity Small Cap | Balanced Strategy vs. Great West Loomis Sayles | Balanced Strategy vs. Vanguard Small Cap Value | Balanced Strategy vs. Amg River Road |
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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 Portfolio Optimization module to compute new portfolio that will generate highest expected return given your specified tolerance for risk.
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