Correlation Between Bank of America and Arima Real
Can any of the company-specific risk be diversified away by investing in both Bank of America and Arima Real 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 Arima Real 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 Arima Real Estate, you can compare the effects of market volatilities on Bank of America and Arima Real 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 Arima Real. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of America and Arima Real.
Diversification Opportunities for Bank of America and Arima Real
0.08 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Bank and Arima is 0.08. Overlapping area represents the amount of risk that can be diversified away by holding Bank of America and Arima Real Estate in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Arima Real Estate 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 Arima Real. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Arima Real Estate has no effect on the direction of Bank of America i.e., Bank of America and Arima Real go up and down completely randomly.
Pair Corralation between Bank of America and Arima Real
Considering the 90-day investment horizon Bank of America is expected to generate 2.63 times more return on investment than Arima Real. However, Bank of America is 2.63 times more volatile than Arima Real Estate. It trades about 0.17 of its potential returns per unit of risk. Arima Real Estate is currently generating about -0.04 per unit of risk. If you would invest 4,044 in Bank of America on August 31, 2024 and sell it today you would earn a total of 733.00 from holding Bank of America or generate 18.13% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 98.44% |
| Values | Daily Returns |
Bank of America vs. Arima Real Estate
Performance |
| Timeline |
| Bank of America |
| Arima Real Estate |
Bank of America and Arima Real Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bank of America and Arima Real
The main advantage of trading using opposite Bank of America and Arima Real positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of America position performs unexpectedly, Arima Real 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 Arima Real will offset losses from the drop in Arima Real's long position.| Bank of America vs. RLJ Lodging Trust | Bank of America vs. Aquagold International | Bank of America vs. Stepstone Group | Bank of America vs. Morningstar Unconstrained Allocation |
| Arima Real vs. Lar Espana Real | Arima Real vs. Inmobiliaria Colonial SA | Arima Real vs. Aedas Homes SL | Arima Real vs. Metrovacesa SA |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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