Correlation Between First Trust and Innovator Long
Can any of the company-specific risk be diversified away by investing in both First Trust and Innovator Long 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 Innovator Long into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between First Trust Cboe and Innovator Long Term, you can compare the effects of market volatilities on First Trust and Innovator Long 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 Innovator Long. Check out your portfolio center. Please also check ongoing floating volatility patterns of First Trust and Innovator Long.
Diversification Opportunities for First Trust and Innovator Long
-0.72 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between First and Innovator is -0.72. Overlapping area represents the amount of risk that can be diversified away by holding First Trust Cboe and Innovator Long Term in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Innovator Long Term 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 Cboe are associated (or correlated) with Innovator Long. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Innovator Long Term has no effect on the direction of First Trust i.e., First Trust and Innovator Long go up and down completely randomly.
Pair Corralation between First Trust and Innovator Long
Given the investment horizon of 90 days First Trust Cboe is expected to generate 0.7 times more return on investment than Innovator Long. However, First Trust Cboe is 1.43 times less risky than Innovator Long. It trades about 0.1 of its potential returns per unit of risk. Innovator Long Term is currently generating about -0.02 per unit of risk. If you would invest 2,890 in First Trust Cboe on September 23, 2024 and sell it today you would earn a total of 162.00 from holding First Trust Cboe or generate 5.61% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
First Trust Cboe vs. Innovator Long Term
Performance |
Timeline |
First Trust Cboe |
Innovator Long Term |
First Trust and Innovator Long Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with First Trust and Innovator Long
The main advantage of trading using opposite First Trust and Innovator Long positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if First Trust position performs unexpectedly, Innovator Long 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 Innovator Long will offset losses from the drop in Innovator Long's long position.First Trust vs. First Trust Exchange Traded | First Trust vs. First Trust Exchange Traded | First Trust vs. FT Cboe Vest | First Trust vs. FT Cboe Vest |
Innovator Long vs. Innovator 20 Year | Innovator Long vs. Northern Lights | Innovator Long vs. iShares 25 Year | Innovator Long vs. First Trust Exchange Traded |
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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