Correlation Between Bank of America and Vanguard FTSE
Can any of the company-specific risk be diversified away by investing in both Bank of America and Vanguard FTSE 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 Bank of America and Vanguard FTSE into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank of America and Vanguard FTSE All World, you can compare the effects of market volatilities on Bank of America and Vanguard FTSE 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 Bank of America with a short position of Vanguard FTSE. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of America and Vanguard FTSE.
Diversification Opportunities for Bank of America and Vanguard FTSE
0.85 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Bank and Vanguard is 0.85. Overlapping area represents the amount of risk that can be diversified away by holding Bank of America and Vanguard FTSE All World in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Vanguard FTSE All and Bank of America 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 Bank of America are associated (or correlated) with Vanguard FTSE. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Vanguard FTSE All has no effect on the direction of Bank of America i.e., Bank of America and Vanguard FTSE go up and down completely randomly.
Pair Corralation between Bank of America and Vanguard FTSE
Considering the 90-day investment horizon Bank of America is expected to generate 2.66 times more return on investment than Vanguard FTSE. However, Bank of America is 2.66 times more volatile than Vanguard FTSE All World. It trades about 0.26 of its potential returns per unit of risk. Vanguard FTSE All World is currently generating about 0.15 per unit of risk. If you would invest 4,262 in Bank of America on August 29, 2024 and sell it today you would earn a total of 515.00 from holding Bank of America or generate 12.08% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Bank of America vs. Vanguard FTSE All World
Performance |
| Timeline |
| Bank of America |
| Vanguard FTSE All |
Bank of America and Vanguard FTSE Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bank of America and Vanguard FTSE
The main advantage of trading using opposite Bank of America and Vanguard FTSE positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of America position performs unexpectedly, Vanguard FTSE 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 Vanguard FTSE will offset losses from the drop in Vanguard FTSE's long position.| Bank of America vs. Citigroup | Bank of America vs. Wells Fargo | Bank of America vs. Toronto Dominion Bank | Bank of America vs. JPMorgan Chase Co |
| Vanguard FTSE vs. iShares II Public | Vanguard FTSE vs. iShares Core MSCI | Vanguard FTSE vs. iShares SP 500 |
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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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