Correlation Between Bank of America and SUNRISE RESOURCES
Can any of the company-specific risk be diversified away by investing in both Bank of America and SUNRISE RESOURCES 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 SUNRISE RESOURCES 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 SUNRISE RESOURCES, you can compare the effects of market volatilities on Bank of America and SUNRISE RESOURCES 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 SUNRISE RESOURCES. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of America and SUNRISE RESOURCES.
Diversification Opportunities for Bank of America and SUNRISE RESOURCES
0.0 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Bank and SUNRISE is 0.0. Overlapping area represents the amount of risk that can be diversified away by holding Bank of America and SUNRISE RESOURCES in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SUNRISE RESOURCES 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 SUNRISE RESOURCES. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SUNRISE RESOURCES has no effect on the direction of Bank of America i.e., Bank of America and SUNRISE RESOURCES go up and down completely randomly.
Pair Corralation between Bank of America and SUNRISE RESOURCES
Considering the 90-day investment horizon Bank of America is expected to generate 22.81 times less return on investment than SUNRISE RESOURCES. But when comparing it to its historical volatility, Bank of America is 27.44 times less risky than SUNRISE RESOURCES. It trades about 0.06 of its potential returns per unit of risk. SUNRISE RESOURCES is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 0.10 in SUNRISE RESOURCES on August 30, 2024 and sell it today you would lose (0.05) from holding SUNRISE RESOURCES or give up 50.0% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Flat |
| Strength | Insignificant |
| Accuracy | 98.21% |
| Values | Daily Returns |
Bank of America vs. SUNRISE RESOURCES
Performance |
| Timeline |
| Bank of America |
| SUNRISE RESOURCES |
Bank of America and SUNRISE RESOURCES Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bank of America and SUNRISE RESOURCES
The main advantage of trading using opposite Bank of America and SUNRISE RESOURCES positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of America position performs unexpectedly, SUNRISE RESOURCES 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 SUNRISE RESOURCES will offset losses from the drop in SUNRISE RESOURCES'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 |
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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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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