Correlation Between Doubleline Core and Gmo Core
Can any of the company-specific risk be diversified away by investing in both Doubleline Core and Gmo Core 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 Doubleline Core and Gmo Core into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Doubleline E Fixed and Gmo E Plus, you can compare the effects of market volatilities on Doubleline Core and Gmo Core 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 Doubleline Core with a short position of Gmo Core. Check out your portfolio center. Please also check ongoing floating volatility patterns of Doubleline Core and Gmo Core.
Diversification Opportunities for Doubleline Core and Gmo Core
1.0 | Correlation Coefficient |
No risk reduction
The 3 months correlation between DOUBLELINE and Gmo is 1.0. Overlapping area represents the amount of risk that can be diversified away by holding Doubleline E Fixed and Gmo E Plus in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Gmo E Plus and Doubleline Core 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 Doubleline E Fixed are associated (or correlated) with Gmo Core. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Gmo E Plus has no effect on the direction of Doubleline Core i.e., Doubleline Core and Gmo Core go up and down completely randomly.
Pair Corralation between Doubleline Core and Gmo Core
Assuming the 90 days horizon Doubleline Core is expected to generate 1.16 times less return on investment than Gmo Core. But when comparing it to its historical volatility, Doubleline E Fixed is 1.02 times less risky than Gmo Core. It trades about 0.14 of its potential returns per unit of risk. Gmo E Plus is currently generating about 0.16 of returns per unit of risk over similar time horizon. If you would invest 1,698 in Gmo E Plus on December 30, 2024 and sell it today you would earn a total of 48.00 from holding Gmo E Plus or generate 2.83% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Doubleline E Fixed vs. Gmo E Plus
Performance |
Timeline |
Doubleline E Fixed |
Gmo E Plus |
Doubleline Core and Gmo Core Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Doubleline Core and Gmo Core
The main advantage of trading using opposite Doubleline Core and Gmo Core positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Doubleline Core position performs unexpectedly, Gmo Core 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 Gmo Core will offset losses from the drop in Gmo Core's long position.Doubleline Core vs. Doubleline Strategic Modity | Doubleline Core vs. Doubleline Emerging Markets | Doubleline Core vs. Doubleline Emerging Markets | Doubleline Core vs. Doubleline Floating Rate |
Gmo Core vs. Ishares Aggregate Bond | Gmo Core vs. Multisector Bond Sma | Gmo Core vs. Ab Bond Inflation | Gmo Core vs. Doubleline Total Return |
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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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