Correlation Between Fly E and Bank of America
Can any of the company-specific risk be diversified away by investing in both Fly E and Bank of America 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 Fly E and Bank of America into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Fly E Group, Common and Bank of America, you can compare the effects of market volatilities on Fly E and Bank of America 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 Fly E with a short position of Bank of America. Check out your portfolio center. Please also check ongoing floating volatility patterns of Fly E and Bank of America.
Diversification Opportunities for Fly E and Bank of America
-0.42 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Fly and Bank is -0.42. Overlapping area represents the amount of risk that can be diversified away by holding Fly E Group, Common and Bank of America in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bank of America and Fly E 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 Fly E Group, Common are associated (or correlated) with Bank of America. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bank of America has no effect on the direction of Fly E i.e., Fly E and Bank of America go up and down completely randomly.
Pair Corralation between Fly E and Bank of America
Given the investment horizon of 90 days Fly E Group, Common is expected to under-perform the Bank of America. In addition to that, Fly E is 11.0 times more volatile than Bank of America. It trades about -0.28 of its total potential returns per unit of risk. Bank of America is currently generating about 0.02 per unit of volatility. If you would invest 2,292 in Bank of America on September 3, 2024 and sell it today you would earn a total of 6.00 from holding Bank of America or generate 0.26% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Fly E Group, Common vs. Bank of America
Performance |
| Timeline |
| Fly E Group, |
| Bank of America |
Fly E and Bank of America Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Fly E and Bank of America
The main advantage of trading using opposite Fly E and Bank of America positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Fly E position performs unexpectedly, Bank of America 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 Bank of America will offset losses from the drop in Bank of America's long position.The idea behind Fly E Group, Common and Bank of America pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.| Bank of America vs. Bank of America | Bank of America vs. Wells Fargo | Bank of America vs. Bank of America | Bank of America vs. China Construction Bank |
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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