Correlation Between Fidelity Flex and Managed Account
Can any of the company-specific risk be diversified away by investing in both Fidelity Flex and Managed Account 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 Fidelity Flex and Managed Account into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Fidelity Flex Servative and Managed Account Series, you can compare the effects of market volatilities on Fidelity Flex and Managed Account 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 Fidelity Flex with a short position of Managed Account. Check out your portfolio center. Please also check ongoing floating volatility patterns of Fidelity Flex and Managed Account.
Diversification Opportunities for Fidelity Flex and Managed Account
0.39 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Fidelity and Managed is 0.39. Overlapping area represents the amount of risk that can be diversified away by holding Fidelity Flex Servative and Managed Account Series in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Managed Account Series and Fidelity Flex 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 Fidelity Flex Servative are associated (or correlated) with Managed Account. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Managed Account Series has no effect on the direction of Fidelity Flex i.e., Fidelity Flex and Managed Account go up and down completely randomly.
Pair Corralation between Fidelity Flex and Managed Account
Assuming the 90 days horizon Fidelity Flex Servative is expected to generate 0.28 times more return on investment than Managed Account. However, Fidelity Flex Servative is 3.54 times less risky than Managed Account. It trades about -0.18 of its potential returns per unit of risk. Managed Account Series is currently generating about -0.43 per unit of risk. If you would invest 1,004 in Fidelity Flex Servative on October 7, 2024 and sell it today you would lose (2.00) from holding Fidelity Flex Servative or give up 0.2% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Fidelity Flex Servative vs. Managed Account Series
Performance |
Timeline |
Fidelity Flex Servative |
Managed Account Series |
Fidelity Flex and Managed Account Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Fidelity Flex and Managed Account
The main advantage of trading using opposite Fidelity Flex and Managed Account positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Fidelity Flex position performs unexpectedly, Managed Account 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 Managed Account will offset losses from the drop in Managed Account's long position.Fidelity Flex vs. Alpine Dynamic Dividend | Fidelity Flex vs. Alpine Global Infrastructure | Fidelity Flex vs. HUMANA INC | Fidelity Flex vs. Aquagold International |
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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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