Correlation Between Legg Mason and Fidelity Managed
Can any of the company-specific risk be diversified away by investing in both Legg Mason and Fidelity Managed 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 Legg Mason and Fidelity Managed into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Legg Mason Partners and Fidelity Managed Retirement, you can compare the effects of market volatilities on Legg Mason and Fidelity Managed 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 Legg Mason with a short position of Fidelity Managed. Check out your portfolio center. Please also check ongoing floating volatility patterns of Legg Mason and Fidelity Managed.
Diversification Opportunities for Legg Mason and Fidelity Managed
0.55 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Legg and Fidelity is 0.55. Overlapping area represents the amount of risk that can be diversified away by holding Legg Mason Partners and Fidelity Managed Retirement in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Fidelity Managed Ret and Legg Mason 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 Legg Mason Partners are associated (or correlated) with Fidelity Managed. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Fidelity Managed Ret has no effect on the direction of Legg Mason i.e., Legg Mason and Fidelity Managed go up and down completely randomly.
Pair Corralation between Legg Mason and Fidelity Managed
Assuming the 90 days trading horizon Legg Mason Partners is expected to generate 1.84 times more return on investment than Fidelity Managed. However, Legg Mason is 1.84 times more volatile than Fidelity Managed Retirement. It trades about 0.08 of its potential returns per unit of risk. Fidelity Managed Retirement is currently generating about 0.05 per unit of risk. If you would invest 1,104 in Legg Mason Partners on October 5, 2024 and sell it today you would earn a total of 278.00 from holding Legg Mason Partners or generate 25.18% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 99.8% |
Values | Daily Returns |
Legg Mason Partners vs. Fidelity Managed Retirement
Performance |
Timeline |
Legg Mason Partners |
Fidelity Managed Ret |
Legg Mason and Fidelity Managed Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Legg Mason and Fidelity Managed
The main advantage of trading using opposite Legg Mason and Fidelity Managed positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Legg Mason position performs unexpectedly, Fidelity Managed 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 Fidelity Managed will offset losses from the drop in Fidelity Managed's long position.Legg Mason vs. International Investors Gold | Legg Mason vs. Fidelity Advisor Gold | Legg Mason vs. Vy Goldman Sachs | Legg Mason vs. Great West Goldman Sachs |
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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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