Correlation Between First Trust and Kurv Yield
Can any of the company-specific risk be diversified away by investing in both First Trust and Kurv Yield 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 First Trust and Kurv Yield into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between First Trust Dorsey and Kurv Yield Premium, you can compare the effects of market volatilities on First Trust and Kurv Yield 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 First Trust with a short position of Kurv Yield. Check out your portfolio center. Please also check ongoing floating volatility patterns of First Trust and Kurv Yield.
Diversification Opportunities for First Trust and Kurv Yield
0.62 | Correlation Coefficient |
Poor diversification
The 3 months correlation between First and Kurv is 0.62. Overlapping area represents the amount of risk that can be diversified away by holding First Trust Dorsey and Kurv Yield Premium in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kurv Yield Premium and First Trust 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 First Trust Dorsey are associated (or correlated) with Kurv Yield. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kurv Yield Premium has no effect on the direction of First Trust i.e., First Trust and Kurv Yield go up and down completely randomly.
Pair Corralation between First Trust and Kurv Yield
Allowing for the 90-day total investment horizon First Trust is expected to generate 2.99 times less return on investment than Kurv Yield. But when comparing it to its historical volatility, First Trust Dorsey is 2.48 times less risky than Kurv Yield. It trades about 0.06 of its potential returns per unit of risk. Kurv Yield Premium is currently generating about 0.07 of returns per unit of risk over similar time horizon. If you would invest 2,035 in Kurv Yield Premium on October 6, 2024 and sell it today you would earn a total of 1,035 from holding Kurv Yield Premium or generate 50.86% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
First Trust Dorsey vs. Kurv Yield Premium
Performance |
Timeline |
First Trust Dorsey |
Kurv Yield Premium |
First Trust and Kurv Yield Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with First Trust and Kurv Yield
The main advantage of trading using opposite First Trust and Kurv Yield positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if First Trust position performs unexpectedly, Kurv Yield 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 Kurv Yield will offset losses from the drop in Kurv Yield's long position.First Trust vs. First Trust Dorsey | First Trust vs. Invesco DWA Momentum | First Trust vs. First Trust Capital | First Trust vs. First Trust Large |
Kurv Yield vs. Tidal Trust II | Kurv Yield vs. Tidal Trust II | Kurv Yield vs. Direxion Daily META | Kurv Yield vs. Direxion Daily META |
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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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