Correlation Between Bank of America and Motorola Solutions
Can any of the company-specific risk be diversified away by investing in both Bank of America and Motorola Solutions 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 Motorola Solutions 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 Motorola Solutions, you can compare the effects of market volatilities on Bank of America and Motorola Solutions 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 Motorola Solutions. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of America and Motorola Solutions.
Diversification Opportunities for Bank of America and Motorola Solutions
0.95 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Bank and Motorola is 0.95. Overlapping area represents the amount of risk that can be diversified away by holding Bank of America and Motorola Solutions in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Motorola Solutions 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 Motorola Solutions. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Motorola Solutions has no effect on the direction of Bank of America i.e., Bank of America and Motorola Solutions go up and down completely randomly.
Pair Corralation between Bank of America and Motorola Solutions
Considering the 90-day investment horizon Bank of America is expected to generate 1.04 times less return on investment than Motorola Solutions. In addition to that, Bank of America is 1.01 times more volatile than Motorola Solutions. It trades about 0.31 of its total potential returns per unit of risk. Motorola Solutions is currently generating about 0.33 per unit of volatility. If you would invest 41,450 in Motorola Solutions on September 1, 2024 and sell it today you would earn a total of 6,190 from holding Motorola Solutions or generate 14.93% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 95.45% |
Values | Daily Returns |
Bank of America vs. Motorola Solutions
Performance |
Timeline |
Bank of America |
Motorola Solutions |
Bank of America and Motorola Solutions Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bank of America and Motorola Solutions
The main advantage of trading using opposite Bank of America and Motorola Solutions positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of America position performs unexpectedly, Motorola Solutions 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 Motorola Solutions will offset losses from the drop in Motorola Solutions' long position.Bank of America vs. Citigroup | Bank of America vs. Toronto Dominion Bank | Bank of America vs. Royal Bank of | Bank of America vs. Nu Holdings |
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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 Analyst Advice module to analyst recommendations and target price estimates broken down by several categories.
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