Correlation Between Bank of America and Wharf Real
Can any of the company-specific risk be diversified away by investing in both Bank of America and Wharf 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 Wharf 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 Wharf Real Estate, you can compare the effects of market volatilities on Bank of America and Wharf 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 Wharf Real. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of America and Wharf Real.
Diversification Opportunities for Bank of America and Wharf Real
-0.27 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Bank and Wharf is -0.27. Overlapping area represents the amount of risk that can be diversified away by holding Bank of America and Wharf Real Estate in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Wharf 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 Wharf Real. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Wharf Real Estate has no effect on the direction of Bank of America i.e., Bank of America and Wharf Real go up and down completely randomly.
Pair Corralation between Bank of America and Wharf Real
Considering the 90-day investment horizon Bank of America is expected to generate 49.07 times less return on investment than Wharf Real. But when comparing it to its historical volatility, Bank of America is 22.42 times less risky than Wharf Real. It trades about 0.06 of its potential returns per unit of risk. Wharf Real Estate is currently generating about 0.14 of returns per unit of risk over similar time horizon. If you would invest 500.00 in Wharf Real Estate on August 28, 2024 and sell it today you would lose (247.00) from holding Wharf Real Estate or give up 49.4% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 75.56% |
| Values | Daily Returns |
Bank of America vs. Wharf Real Estate
Performance |
| Timeline |
| Bank of America |
| Wharf Real Estate |
Bank of America and Wharf Real Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bank of America and Wharf Real
The main advantage of trading using opposite Bank of America and Wharf Real positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of America position performs unexpectedly, Wharf 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 Wharf Real will offset losses from the drop in Wharf Real's long position.| Bank of America vs. Nu Holdings | Bank of America vs. HSBC Holdings PLC | Bank of America vs. Bank of Montreal | Bank of America vs. Bank of Nova |
| Wharf Real vs. Maui Land Pineapple | Wharf Real vs. Marcus Millichap | Wharf Real vs. Frp Holdings Ord | Wharf Real vs. Anywhere Real Estate |
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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