Correlation Between Eagle Mlp and Putnam Floating
Can any of the company-specific risk be diversified away by investing in both Eagle Mlp and Putnam Floating 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 Putnam Floating 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 Putnam Floating Rate, you can compare the effects of market volatilities on Eagle Mlp and Putnam Floating 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 Putnam Floating. Check out your portfolio center. Please also check ongoing floating volatility patterns of Eagle Mlp and Putnam Floating.
Diversification Opportunities for Eagle Mlp and Putnam Floating
0.89 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Eagle and Putnam is 0.89. Overlapping area represents the amount of risk that can be diversified away by holding Eagle Mlp Strategy and Putnam Floating Rate in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Putnam Floating Rate 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 Putnam Floating. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Putnam Floating Rate has no effect on the direction of Eagle Mlp i.e., Eagle Mlp and Putnam Floating go up and down completely randomly.
Pair Corralation between Eagle Mlp and Putnam Floating
Assuming the 90 days horizon Eagle Mlp Strategy is expected to generate 6.48 times more return on investment than Putnam Floating. However, Eagle Mlp is 6.48 times more volatile than Putnam Floating Rate. It trades about 0.23 of its potential returns per unit of risk. Putnam Floating Rate is currently generating about 0.2 per unit of risk. If you would invest 838.00 in Eagle Mlp Strategy on September 3, 2024 and sell it today you would earn a total of 293.00 from holding Eagle Mlp Strategy or generate 34.96% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Eagle Mlp Strategy vs. Putnam Floating Rate
Performance |
| Timeline |
| Eagle Mlp Strategy |
| Putnam Floating Rate |
Eagle Mlp and Putnam Floating Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Eagle Mlp and Putnam Floating
The main advantage of trading using opposite Eagle Mlp and Putnam Floating positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Eagle Mlp position performs unexpectedly, Putnam Floating 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 Putnam Floating will offset losses from the drop in Putnam Floating's long position.| Eagle Mlp vs. Artisan High Income | Eagle Mlp vs. Gmo High Yield | Eagle Mlp vs. Ambrus Core Bond | Eagle Mlp vs. Rationalpier 88 Convertible |
| Putnam Floating vs. Rbb Fund | Putnam Floating vs. Fa 529 Aggressive | Putnam Floating vs. Volumetric Fund Volumetric | Putnam Floating vs. Arrow Managed Futures |
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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