Correlation Between Bank of America and Banco Santander
Can any of the company-specific risk be diversified away by investing in both Bank of America and Banco Santander 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 Banco Santander 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 Banco Santander SA, you can compare the effects of market volatilities on Bank of America and Banco Santander 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 Banco Santander. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of America and Banco Santander.
Diversification Opportunities for Bank of America and Banco Santander
0.81 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Bank and Banco is 0.81. Overlapping area represents the amount of risk that can be diversified away by holding Bank of America and Banco Santander SA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Banco Santander SA 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 Banco Santander. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Banco Santander SA has no effect on the direction of Bank of America i.e., Bank of America and Banco Santander go up and down completely randomly.
Pair Corralation between Bank of America and Banco Santander
Assuming the 90 days trading horizon Bank of America is expected to generate 3.9 times less return on investment than Banco Santander. But when comparing it to its historical volatility, Bank of America is 1.95 times less risky than Banco Santander. It trades about 0.04 of its potential returns per unit of risk. Banco Santander SA is currently generating about 0.07 of returns per unit of risk over similar time horizon. If you would invest 490.00 in Banco Santander SA on August 7, 2024 and sell it today you would earn a total of 8.00 from holding Banco Santander SA or generate 1.63% 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. Banco Santander SA
Performance |
Timeline |
Bank of America |
Banco Santander SA |
Bank of America and Banco Santander Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bank of America and Banco Santander
The main advantage of trading using opposite Bank of America and Banco Santander positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of America position performs unexpectedly, Banco Santander 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 Banco Santander will offset losses from the drop in Banco Santander's long position.Bank of America vs. China Construction Bank | Bank of America vs. Wells Fargo | Bank of America vs. Bank of America | Bank of America vs. Bank of America |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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