Correlation Between Bank of America and ALPSSmith Balanced
Can any of the company-specific risk be diversified away by investing in both Bank of America and ALPSSmith Balanced 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 ALPSSmith Balanced 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 ALPSSmith Balanced Opportunity, you can compare the effects of market volatilities on Bank of America and ALPSSmith Balanced 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 ALPSSmith Balanced. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of America and ALPSSmith Balanced.
Diversification Opportunities for Bank of America and ALPSSmith Balanced
0.75 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Bank and ALPSSmith is 0.75. Overlapping area represents the amount of risk that can be diversified away by holding Bank of America and ALPSSmith Balanced Opportunity in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on ALPSSmith Balanced 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 ALPSSmith Balanced. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of ALPSSmith Balanced has no effect on the direction of Bank of America i.e., Bank of America and ALPSSmith Balanced go up and down completely randomly.
Pair Corralation between Bank of America and ALPSSmith Balanced
Considering the 90-day investment horizon Bank of America is expected to generate 2.92 times more return on investment than ALPSSmith Balanced. However, Bank of America is 2.92 times more volatile than ALPSSmith Balanced Opportunity. It trades about 0.05 of its potential returns per unit of risk. ALPSSmith Balanced Opportunity is currently generating about 0.1 per unit of risk. If you would invest 3,278 in Bank of America on August 24, 2024 and sell it today you would earn a total of 1,422 from holding Bank of America or generate 43.38% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Bank of America vs. ALPSSmith Balanced Opportunity
Performance |
| Timeline |
| Bank of America |
| ALPSSmith Balanced |
Bank of America and ALPSSmith Balanced Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bank of America and ALPSSmith Balanced
The main advantage of trading using opposite Bank of America and ALPSSmith Balanced positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of America position performs unexpectedly, ALPSSmith Balanced 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 ALPSSmith Balanced will offset losses from the drop in ALPSSmith Balanced's long position.| Bank of America vs. Amtech Systems | Bank of America vs. Gold Fields Ltd | Bank of America vs. Aegean Airlines SA | Bank of America vs. Merck Company |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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