Correlation Between Bank of America and Baillie Gifford
Can any of the company-specific risk be diversified away by investing in both Bank of America and Baillie Gifford 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 Baillie Gifford 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 Baillie Gifford China, you can compare the effects of market volatilities on Bank of America and Baillie Gifford 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 Baillie Gifford. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of America and Baillie Gifford.
Diversification Opportunities for Bank of America and Baillie Gifford
0.25 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Bank and Baillie is 0.25. Overlapping area represents the amount of risk that can be diversified away by holding Bank of America and Baillie Gifford China in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Baillie Gifford China 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 Baillie Gifford. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Baillie Gifford China has no effect on the direction of Bank of America i.e., Bank of America and Baillie Gifford go up and down completely randomly.
Pair Corralation between Bank of America and Baillie Gifford
Considering the 90-day investment horizon Bank of America is expected to generate 1.0 times more return on investment than Baillie Gifford. However, Bank of America is 1.0 times more volatile than Baillie Gifford China. It trades about 0.06 of its potential returns per unit of risk. Baillie Gifford China is currently generating about -0.01 per unit of risk. If you would invest 3,113 in Bank of America on September 2, 2024 and sell it today you would earn a total of 1,638 from holding Bank of America or generate 52.62% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Bank of America vs. Baillie Gifford China
Performance |
Timeline |
Bank of America |
Baillie Gifford China |
Bank of America and Baillie Gifford Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bank of America and Baillie Gifford
The main advantage of trading using opposite Bank of America and Baillie Gifford positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of America position performs unexpectedly, Baillie Gifford 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 Baillie Gifford will offset losses from the drop in Baillie Gifford's long position.Bank of America vs. Citigroup | Bank of America vs. Nu Holdings | Bank of America vs. HSBC Holdings PLC | Bank of America vs. Bank of Montreal |
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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 Alpha Finder module to use alpha and beta coefficients to find investment opportunities after accounting for the risk.
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