Correlation Between IPath Series and Amplify CWP
Can any of the company-specific risk be diversified away by investing in both IPath Series and Amplify CWP 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 Amplify CWP 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 Amplify CWP Enhanced, you can compare the effects of market volatilities on IPath Series and Amplify CWP 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 Amplify CWP. Check out your portfolio center. Please also check ongoing floating volatility patterns of IPath Series and Amplify CWP.
Diversification Opportunities for IPath Series and Amplify CWP
-0.68 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between IPath and Amplify is -0.68. Overlapping area represents the amount of risk that can be diversified away by holding iPath Series B and Amplify CWP Enhanced in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Amplify CWP Enhanced 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 Amplify CWP. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Amplify CWP Enhanced has no effect on the direction of IPath Series i.e., IPath Series and Amplify CWP go up and down completely randomly.
Pair Corralation between IPath Series and Amplify CWP
Considering the 90-day investment horizon iPath Series B is expected to under-perform the Amplify CWP. In addition to that, IPath Series is 7.51 times more volatile than Amplify CWP Enhanced. It trades about -0.05 of its total potential returns per unit of risk. Amplify CWP Enhanced is currently generating about 0.09 per unit of volatility. If you would invest 3,276 in Amplify CWP Enhanced on October 24, 2024 and sell it today you would earn a total of 909.00 from holding Amplify CWP Enhanced or generate 27.75% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
iPath Series B vs. Amplify CWP Enhanced
Performance |
Timeline |
iPath Series B |
Amplify CWP Enhanced |
IPath Series and Amplify CWP Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with IPath Series and Amplify CWP
The main advantage of trading using opposite IPath Series and Amplify CWP positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if IPath Series position performs unexpectedly, Amplify CWP 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 Amplify CWP will offset losses from the drop in Amplify CWP'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 |
Amplify CWP vs. NEOS ETF Trust | Amplify CWP vs. Global X SP | Amplify CWP vs. Global X Russell | Amplify CWP vs. JPMorgan Equity Premium |
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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