Correlation Between ProShares Ultra and IPath Series
Can any of the company-specific risk be diversified away by investing in both ProShares Ultra and IPath Series 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 IPath Series into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between ProShares Ultra VIX and iPath Series B, you can compare the effects of market volatilities on ProShares Ultra and IPath Series 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 IPath Series. Check out your portfolio center. Please also check ongoing floating volatility patterns of ProShares Ultra and IPath Series.
Diversification Opportunities for ProShares Ultra and IPath Series
0.99 | Correlation Coefficient |
No risk reduction
The 3 months correlation between ProShares and IPath is 0.99. Overlapping area represents the amount of risk that can be diversified away by holding ProShares Ultra VIX and iPath Series B in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on iPath Series B 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 VIX are associated (or correlated) with IPath Series. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of iPath Series B has no effect on the direction of ProShares Ultra i.e., ProShares Ultra and IPath Series go up and down completely randomly.
Pair Corralation between ProShares Ultra and IPath Series
Given the investment horizon of 90 days ProShares Ultra is expected to generate 1.12 times less return on investment than IPath Series. In addition to that, ProShares Ultra is 1.49 times more volatile than iPath Series B. It trades about 0.0 of its total potential returns per unit of risk. iPath Series B is currently generating about 0.01 per unit of volatility. If you would invest 5,424 in iPath Series B on August 27, 2024 and sell it today you would lose (848.00) from holding iPath Series B or give up 15.63% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
ProShares Ultra VIX vs. iPath Series B
Performance |
| Timeline |
| ProShares Ultra VIX |
| iPath Series B |
ProShares Ultra and IPath Series Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with ProShares Ultra and IPath Series
The main advantage of trading using opposite ProShares Ultra and IPath Series positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if ProShares Ultra position performs unexpectedly, IPath Series 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 IPath Series will offset losses from the drop in IPath Series' long position.| ProShares Ultra vs. ProShares UltraPro Short | ProShares Ultra vs. ProShares Short VIX | ProShares Ultra vs. iPath Series B |
| IPath Series vs. ProShares Ultra VIX | IPath Series vs. ProShares Short VIX | IPath Series vs. ProShares UltraPro Short | IPath Series vs. iShares 20 Year |
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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