Correlation Between ProShares Ultra and UBS ETRACS
Can any of the company-specific risk be diversified away by investing in both ProShares Ultra and UBS ETRACS 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 ProShares Ultra and UBS ETRACS into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between ProShares Ultra Bloomberg and UBS ETRACS , you can compare the effects of market volatilities on ProShares Ultra and UBS ETRACS 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 ProShares Ultra with a short position of UBS ETRACS. Check out your portfolio center. Please also check ongoing floating volatility patterns of ProShares Ultra and UBS ETRACS.
Diversification Opportunities for ProShares Ultra and UBS ETRACS
0.0 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between ProShares and UBS is 0.0. Overlapping area represents the amount of risk that can be diversified away by holding ProShares Ultra Bloomberg and UBS ETRACS in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on UBS ETRACS and ProShares Ultra 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 ProShares Ultra Bloomberg are associated (or correlated) with UBS ETRACS. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of UBS ETRACS has no effect on the direction of ProShares Ultra i.e., ProShares Ultra and UBS ETRACS go up and down completely randomly.
Pair Corralation between ProShares Ultra and UBS ETRACS
Given the investment horizon of 90 days ProShares Ultra Bloomberg is expected to under-perform the UBS ETRACS. In addition to that, ProShares Ultra is 1.67 times more volatile than UBS ETRACS . It trades about -0.05 of its total potential returns per unit of risk. UBS ETRACS is currently generating about 0.02 per unit of volatility. If you would invest 2,327 in UBS ETRACS on September 24, 2024 and sell it today you would earn a total of 9.00 from holding UBS ETRACS or generate 0.39% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Flat |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
ProShares Ultra Bloomberg vs. UBS ETRACS
Performance |
Timeline |
ProShares Ultra Bloomberg |
UBS ETRACS |
ProShares Ultra and UBS ETRACS Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with ProShares Ultra and UBS ETRACS
The main advantage of trading using opposite ProShares Ultra and UBS ETRACS positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if ProShares Ultra position performs unexpectedly, UBS ETRACS 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 UBS ETRACS will offset losses from the drop in UBS ETRACS's long position.ProShares Ultra vs. Ultimus Managers Trust | ProShares Ultra vs. Direxion Daily SP | ProShares Ultra vs. EA Series Trust | ProShares Ultra vs. Global X MLP |
UBS ETRACS vs. ProShares Ultra Bloomberg | UBS ETRACS vs. Direxion Daily Semiconductor | UBS ETRACS vs. Direxion Daily SP |
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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