Correlation Between CREDIT AGRICOLE and Bank of America
Can any of the company-specific risk be diversified away by investing in both CREDIT AGRICOLE 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 CREDIT AGRICOLE 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 CREDIT AGRICOLE and Verizon Communications, you can compare the effects of market volatilities on CREDIT AGRICOLE 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 CREDIT AGRICOLE with a short position of Bank of America. Check out your portfolio center. Please also check ongoing floating volatility patterns of CREDIT AGRICOLE and Bank of America.
Diversification Opportunities for CREDIT AGRICOLE and Bank of America
0.76 | Correlation Coefficient |
Poor diversification
The 3 months correlation between CREDIT and Bank is 0.76. Overlapping area represents the amount of risk that can be diversified away by holding CREDIT AGRICOLE and Verizon Communications in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Verizon Communications and CREDIT AGRICOLE 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 CREDIT AGRICOLE 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 Verizon Communications has no effect on the direction of CREDIT AGRICOLE i.e., CREDIT AGRICOLE and Bank of America go up and down completely randomly.
Pair Corralation between CREDIT AGRICOLE and Bank of America
Assuming the 90 days trading horizon CREDIT AGRICOLE is expected to generate 0.57 times more return on investment than Bank of America. However, CREDIT AGRICOLE is 1.76 times less risky than Bank of America. It trades about 0.42 of its potential returns per unit of risk. Verizon Communications is currently generating about 0.07 per unit of risk. If you would invest 1,300 in CREDIT AGRICOLE on December 21, 2024 and sell it today you would earn a total of 387.00 from holding CREDIT AGRICOLE or generate 29.77% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
CREDIT AGRICOLE vs. Verizon Communications
Performance |
Timeline |
CREDIT AGRICOLE |
Verizon Communications |
CREDIT AGRICOLE and Bank of America Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with CREDIT AGRICOLE and Bank of America
The main advantage of trading using opposite CREDIT AGRICOLE and Bank of America positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if CREDIT AGRICOLE 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.CREDIT AGRICOLE vs. Chesapeake Utilities | CREDIT AGRICOLE vs. UNITED UTILITIES GR | CREDIT AGRICOLE vs. AviChina Industry Technology | CREDIT AGRICOLE vs. EITZEN CHEMICALS |
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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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