Correlation Between SSGA Active and Return Stacked
Can any of the company-specific risk be diversified away by investing in both SSGA Active and Return Stacked 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 SSGA Active and Return Stacked into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SSGA Active Trust and Return Stacked Bonds, you can compare the effects of market volatilities on SSGA Active and Return Stacked 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 SSGA Active with a short position of Return Stacked. Check out your portfolio center. Please also check ongoing floating volatility patterns of SSGA Active and Return Stacked.
Diversification Opportunities for SSGA Active and Return Stacked
-0.09 | Correlation Coefficient |
Good diversification
The 3 months correlation between SSGA and Return is -0.09. Overlapping area represents the amount of risk that can be diversified away by holding SSGA Active Trust and Return Stacked Bonds in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Return Stacked Bonds and SSGA Active 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 SSGA Active Trust are associated (or correlated) with Return Stacked. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Return Stacked Bonds has no effect on the direction of SSGA Active i.e., SSGA Active and Return Stacked go up and down completely randomly.
Pair Corralation between SSGA Active and Return Stacked
Given the investment horizon of 90 days SSGA Active Trust is expected to generate 0.26 times more return on investment than Return Stacked. However, SSGA Active Trust is 3.84 times less risky than Return Stacked. It trades about 0.12 of its potential returns per unit of risk. Return Stacked Bonds is currently generating about 0.02 per unit of risk. If you would invest 2,544 in SSGA Active Trust on December 28, 2024 and sell it today you would earn a total of 39.00 from holding SSGA Active Trust or generate 1.53% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 98.36% |
Values | Daily Returns |
SSGA Active Trust vs. Return Stacked Bonds
Performance |
Timeline |
SSGA Active Trust |
Return Stacked Bonds |
SSGA Active and Return Stacked Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with SSGA Active and Return Stacked
The main advantage of trading using opposite SSGA Active and Return Stacked positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SSGA Active position performs unexpectedly, Return Stacked 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 Return Stacked will offset losses from the drop in Return Stacked's long position.SSGA Active vs. SPDR Bloomberg Barclays | SSGA Active vs. SPDR SSGA Fixed | SSGA Active vs. SPDR DoubleLine Short | SSGA Active vs. SPDR Portfolio Corporate |
Return Stacked vs. KFA Mount Lucas | Return Stacked vs. iMGP DBi Managed | Return Stacked vs. Simplify Exchange Traded | Return Stacked vs. Tidal ETF Trust |
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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