Correlation Between IPath Series and SPDR Galaxy
Can any of the company-specific risk be diversified away by investing in both IPath Series and SPDR Galaxy 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 IPath Series and SPDR Galaxy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between iPath Series B and SPDR Galaxy Digital, you can compare the effects of market volatilities on IPath Series and SPDR Galaxy 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 IPath Series with a short position of SPDR Galaxy. Check out your portfolio center. Please also check ongoing floating volatility patterns of IPath Series and SPDR Galaxy.
Diversification Opportunities for IPath Series and SPDR Galaxy
-0.8 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between IPath and SPDR is -0.8. Overlapping area represents the amount of risk that can be diversified away by holding iPath Series B and SPDR Galaxy Digital in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SPDR Galaxy Digital and IPath Series 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 iPath Series B are associated (or correlated) with SPDR Galaxy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SPDR Galaxy Digital has no effect on the direction of IPath Series i.e., IPath Series and SPDR Galaxy go up and down completely randomly.
Pair Corralation between IPath Series and SPDR Galaxy
Considering the 90-day investment horizon iPath Series B is expected to under-perform the SPDR Galaxy. In addition to that, IPath Series is 1.05 times more volatile than SPDR Galaxy Digital. It trades about -0.06 of its total potential returns per unit of risk. SPDR Galaxy Digital is currently generating about 0.17 per unit of volatility. If you would invest 3,416 in SPDR Galaxy Digital on October 23, 2024 and sell it today you would earn a total of 350.00 from holding SPDR Galaxy Digital or generate 10.25% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Significant |
| Accuracy | 94.74% |
| Values | Daily Returns |
iPath Series B vs. SPDR Galaxy Digital
Performance |
| Timeline |
| iPath Series B |
| SPDR Galaxy Digital |
IPath Series and SPDR Galaxy Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with IPath Series and SPDR Galaxy
The main advantage of trading using opposite IPath Series and SPDR Galaxy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if IPath Series position performs unexpectedly, SPDR Galaxy 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 Galaxy will offset losses from the drop in SPDR Galaxy's long position.| IPath Series vs. ProShares Ultra VIX | IPath Series vs. ProShares Short VIX | IPath Series vs. ProShares UltraPro Short | IPath Series vs. iShares 20 Year |
| SPDR Galaxy vs. iShares Dividend and | SPDR Galaxy vs. Martin Currie Sustainable | SPDR Galaxy vs. VictoryShares THB Mid | SPDR Galaxy vs. Mast Global Battery |
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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