Correlation Between Day HaganNed and SPDR SSGA
Can any of the company-specific risk be diversified away by investing in both Day HaganNed and SPDR SSGA 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 Day HaganNed and SPDR SSGA into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Day HaganNed Davis and SPDR SSGA Sector, you can compare the effects of market volatilities on Day HaganNed and SPDR SSGA 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 Day HaganNed with a short position of SPDR SSGA. Check out your portfolio center. Please also check ongoing floating volatility patterns of Day HaganNed and SPDR SSGA.
Diversification Opportunities for Day HaganNed and SPDR SSGA
0.96 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Day and SPDR is 0.96. Overlapping area represents the amount of risk that can be diversified away by holding Day HaganNed Davis and SPDR SSGA Sector in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SPDR SSGA Sector and Day HaganNed 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 Day HaganNed Davis are associated (or correlated) with SPDR SSGA. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SPDR SSGA Sector has no effect on the direction of Day HaganNed i.e., Day HaganNed and SPDR SSGA go up and down completely randomly.
Pair Corralation between Day HaganNed and SPDR SSGA
Given the investment horizon of 90 days Day HaganNed is expected to generate 1.15 times less return on investment than SPDR SSGA. But when comparing it to its historical volatility, Day HaganNed Davis is 1.12 times less risky than SPDR SSGA. It trades about 0.08 of its potential returns per unit of risk. SPDR SSGA Sector is currently generating about 0.09 of returns per unit of risk over similar time horizon. If you would invest 3,930 in SPDR SSGA Sector on November 28, 2024 and sell it today you would earn a total of 1,474 from holding SPDR SSGA Sector or generate 37.51% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 99.79% |
| Values | Daily Returns |
Day HaganNed Davis vs. SPDR SSGA Sector
Performance |
| Timeline |
| Day HaganNed Davis |
| SPDR SSGA Sector |
Day HaganNed and SPDR SSGA Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Day HaganNed and SPDR SSGA
The main advantage of trading using opposite Day HaganNed and SPDR SSGA positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Day HaganNed position performs unexpectedly, SPDR SSGA 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 SPDR SSGA will offset losses from the drop in SPDR SSGA's long position.| Day HaganNed vs. SPDR SSGA Sector | Day HaganNed vs. Inspire International ESG | Day HaganNed vs. Overlay Shares Large | Day HaganNed vs. Timothy Plan Small |
| SPDR SSGA vs. SPDR SSGA Fixed | SPDR SSGA vs. BlackRock Equity Factor | SPDR SSGA vs. SPDR FactSet Innovative | SPDR SSGA vs. SPDR SP Telecom |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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