Correlation Between SPDR SP and SPDR Bloomberg
Can any of the company-specific risk be diversified away by investing in both SPDR SP and SPDR Bloomberg 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 SPDR SP and SPDR Bloomberg into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SPDR SP Kensho and SPDR Bloomberg Barclays, you can compare the effects of market volatilities on SPDR SP and SPDR Bloomberg 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 SPDR SP with a short position of SPDR Bloomberg. Check out your portfolio center. Please also check ongoing floating volatility patterns of SPDR SP and SPDR Bloomberg.
Diversification Opportunities for SPDR SP and SPDR Bloomberg
-0.06 | Correlation Coefficient |
Good diversification
The 3 months correlation between SPDR and SPDR is -0.06. Overlapping area represents the amount of risk that can be diversified away by holding SPDR SP Kensho and SPDR Bloomberg Barclays in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SPDR Bloomberg Barclays and SPDR SP 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 SPDR SP Kensho are associated (or correlated) with SPDR Bloomberg. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SPDR Bloomberg Barclays has no effect on the direction of SPDR SP i.e., SPDR SP and SPDR Bloomberg go up and down completely randomly.
Pair Corralation between SPDR SP and SPDR Bloomberg
Given the investment horizon of 90 days SPDR SP Kensho is expected to under-perform the SPDR Bloomberg. In addition to that, SPDR SP is 5.58 times more volatile than SPDR Bloomberg Barclays. It trades about -0.04 of its total potential returns per unit of risk. SPDR Bloomberg Barclays is currently generating about 0.34 per unit of volatility. If you would invest 2,797 in SPDR Bloomberg Barclays on December 2, 2024 and sell it today you would earn a total of 54.00 from holding SPDR Bloomberg Barclays or generate 1.93% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
SPDR SP Kensho vs. SPDR Bloomberg Barclays
Performance |
Timeline |
SPDR SP Kensho |
SPDR Bloomberg Barclays |
SPDR SP and SPDR Bloomberg Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with SPDR SP and SPDR Bloomberg
The main advantage of trading using opposite SPDR SP and SPDR Bloomberg positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SPDR SP position performs unexpectedly, SPDR Bloomberg 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 Bloomberg will offset losses from the drop in SPDR Bloomberg's long position.SPDR SP vs. SPDR STOXX Europe | SPDR SP vs. SPDR Bloomberg Barclays | SPDR SP vs. SPDR Kensho Future | SPDR SP vs. SPDR Kensho Intelligent |
SPDR Bloomberg vs. SPDR STOXX Europe | SPDR Bloomberg vs. SPDR Kensho Future | SPDR Bloomberg vs. SPDR Kensho Intelligent | SPDR Bloomberg vs. SPDR SP Kensho |
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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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