Correlation Between FT Cboe and First Trust
Can any of the company-specific risk be diversified away by investing in both FT Cboe and First Trust 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 FT Cboe and First Trust into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between FT Cboe Vest and First Trust Exchange Traded, you can compare the effects of market volatilities on FT Cboe and First Trust 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 FT Cboe with a short position of First Trust. Check out your portfolio center. Please also check ongoing floating volatility patterns of FT Cboe and First Trust.
Diversification Opportunities for FT Cboe and First Trust
0.96 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between FNOV and First is 0.96. Overlapping area represents the amount of risk that can be diversified away by holding FT Cboe Vest and First Trust Exchange Traded in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on First Trust Exchange and FT Cboe 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 FT Cboe Vest are associated (or correlated) with First Trust. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of First Trust Exchange has no effect on the direction of FT Cboe i.e., FT Cboe and First Trust go up and down completely randomly.
Pair Corralation between FT Cboe and First Trust
Given the investment horizon of 90 days FT Cboe is expected to generate 1.02 times less return on investment than First Trust. But when comparing it to its historical volatility, FT Cboe Vest is 1.02 times less risky than First Trust. It trades about 0.17 of its potential returns per unit of risk. First Trust Exchange Traded is currently generating about 0.17 of returns per unit of risk over similar time horizon. If you would invest 3,826 in First Trust Exchange Traded on August 25, 2024 and sell it today you would earn a total of 931.00 from holding First Trust Exchange Traded or generate 24.33% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
FT Cboe Vest vs. First Trust Exchange Traded
Performance |
| Timeline |
| FT Cboe Vest |
| First Trust Exchange |
FT Cboe and First Trust Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with FT Cboe and First Trust
The main advantage of trading using opposite FT Cboe and First Trust positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if FT Cboe position performs unexpectedly, First Trust 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 First Trust will offset losses from the drop in First Trust's long position.| FT Cboe vs. First Trust Cboe | FT Cboe vs. FT Cboe Vest | FT Cboe vs. Innovator SP 500 | FT Cboe vs. Innovator Equity Power |
| First Trust vs. FT Cboe Vest | First Trust vs. FT Cboe Vest | First Trust vs. FT Cboe Vest | First Trust vs. FT Cboe Vest |
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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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