Correlation Between Abrdn Bloomberg and Bank of America
Can any of the company-specific risk be diversified away by investing in both Abrdn Bloomberg 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 Abrdn Bloomberg 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 abrdn Bloomberg All and Bank of America, you can compare the effects of market volatilities on Abrdn Bloomberg 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 Abrdn Bloomberg with a short position of Bank of America. Check out your portfolio center. Please also check ongoing floating volatility patterns of Abrdn Bloomberg and Bank of America.
Diversification Opportunities for Abrdn Bloomberg and Bank of America
0.8 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Abrdn and Bank is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding abrdn Bloomberg All 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 Abrdn Bloomberg 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 abrdn Bloomberg All 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 Abrdn Bloomberg i.e., Abrdn Bloomberg and Bank of America go up and down completely randomly.
Pair Corralation between Abrdn Bloomberg and Bank of America
Considering the 90-day investment horizon abrdn Bloomberg All is expected to under-perform the Bank of America. But the etf apears to be less risky and, when comparing its historical volatility, abrdn Bloomberg All is 1.74 times less risky than Bank of America. The etf trades about -0.02 of its potential returns per unit of risk. The Bank of America is currently generating about 0.01 of returns per unit of risk over similar time horizon. If you would invest 3,481 in Bank of America on January 18, 2024 and sell it today you would earn a total of 42.00 from holding Bank of America or generate 1.21% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
abrdn Bloomberg All vs. Bank of America
Performance |
| Timeline |
| abrdn Bloomberg All |
| Bank of America |
Abrdn Bloomberg and Bank of America Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Abrdn Bloomberg and Bank of America
The main advantage of trading using opposite Abrdn Bloomberg and Bank of America positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Abrdn Bloomberg 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.| Abrdn Bloomberg vs. Invesco DB Agriculture | Abrdn Bloomberg vs. Invesco DB Base | Abrdn Bloomberg vs. VanEck Agribusiness ETF |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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