Correlation Between Bank of America and Retail Food
Can any of the company-specific risk be diversified away by investing in both Bank of America and Retail Food 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 Retail Food 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 Retail Food Group, you can compare the effects of market volatilities on Bank of America and Retail Food 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 Retail Food. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of America and Retail Food.
Diversification Opportunities for Bank of America and Retail Food
0.57 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Bank and Retail is 0.57. Overlapping area represents the amount of risk that can be diversified away by holding Bank of America and Retail Food Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Retail Food Group 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 Retail Food. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Retail Food Group has no effect on the direction of Bank of America i.e., Bank of America and Retail Food go up and down completely randomly.
Pair Corralation between Bank of America and Retail Food
Considering the 90-day investment horizon Bank of America is expected to generate 0.7 times more return on investment than Retail Food. However, Bank of America is 1.43 times less risky than Retail Food. It trades about 0.27 of its potential returns per unit of risk. Retail Food Group is currently generating about 0.18 per unit of risk. If you would invest 4,262 in Bank of America on August 29, 2024 and sell it today you would earn a total of 523.50 from holding Bank of America or generate 12.28% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 95.65% |
| Values | Daily Returns |
Bank of America vs. Retail Food Group
Performance |
| Timeline |
| Bank of America |
| Retail Food Group |
Bank of America and Retail Food Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bank of America and Retail Food
The main advantage of trading using opposite Bank of America and Retail Food positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of America position performs unexpectedly, Retail Food 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 Retail Food will offset losses from the drop in Retail Food's long position.| Bank of America vs. Citigroup | Bank of America vs. Wells Fargo | Bank of America vs. Toronto Dominion Bank | Bank of America vs. JPMorgan Chase Co |
| Retail Food vs. Autosports Group | Retail Food vs. AiMedia Technologies | Retail Food vs. BKI Investment | Retail Food vs. ARN Media Limited |
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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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