Correlation Between Eagle Mlp and American Funds
Can any of the company-specific risk be diversified away by investing in both Eagle Mlp and American Funds 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 Eagle Mlp and American Funds into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Eagle Mlp Strategy and American Funds 2065, you can compare the effects of market volatilities on Eagle Mlp and American Funds 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 Eagle Mlp with a short position of American Funds. Check out your portfolio center. Please also check ongoing floating volatility patterns of Eagle Mlp and American Funds.
Diversification Opportunities for Eagle Mlp and American Funds
0.67 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Eagle and American is 0.67. Overlapping area represents the amount of risk that can be diversified away by holding Eagle Mlp Strategy and American Funds 2065 in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on American Funds 2065 and Eagle Mlp 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 Eagle Mlp Strategy are associated (or correlated) with American Funds. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of American Funds 2065 has no effect on the direction of Eagle Mlp i.e., Eagle Mlp and American Funds go up and down completely randomly.
Pair Corralation between Eagle Mlp and American Funds
Assuming the 90 days horizon Eagle Mlp Strategy is expected to generate 1.4 times more return on investment than American Funds. However, Eagle Mlp is 1.4 times more volatile than American Funds 2065. It trades about 0.12 of its potential returns per unit of risk. American Funds 2065 is currently generating about 0.11 per unit of risk. If you would invest 619.00 in Eagle Mlp Strategy on September 12, 2024 and sell it today you would earn a total of 452.00 from holding Eagle Mlp Strategy or generate 73.02% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Eagle Mlp Strategy vs. American Funds 2065
Performance |
| Timeline |
| Eagle Mlp Strategy |
| American Funds 2065 |
Eagle Mlp and American Funds Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Eagle Mlp and American Funds
The main advantage of trading using opposite Eagle Mlp and American Funds positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Eagle Mlp position performs unexpectedly, American Funds 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 American Funds will offset losses from the drop in American Funds' long position.| Eagle Mlp vs. Oppenheimer Steelpath Mlp | Eagle Mlp vs. Oppenheimer Steelpath Mlp | Eagle Mlp vs. HUMANA INC | Eagle Mlp vs. Barloworld Ltd ADR |
| American Funds vs. Eagle Mlp Strategy | American Funds vs. Black Oak Emerging | American Funds vs. Ep Emerging Markets | American Funds vs. Dws Emerging Markets |
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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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