Correlation Between Bank of America and Ashford
Can any of the company-specific risk be diversified away by investing in both Bank of America and Ashford 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 Ashford 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 Ashford, you can compare the effects of market volatilities on Bank of America and Ashford 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 Ashford. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of America and Ashford.
Diversification Opportunities for Bank of America and Ashford
0.82 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Bank and Ashford is 0.82. Overlapping area represents the amount of risk that can be diversified away by holding Bank of America and Ashford in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ashford 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 Ashford. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ashford has no effect on the direction of Bank of America i.e., Bank of America and Ashford go up and down completely randomly.
Pair Corralation between Bank of America and Ashford
Considering the 90-day investment horizon Bank of America is expected to generate 1.83 times less return on investment than Ashford. But when comparing it to its historical volatility, Bank of America is 6.68 times less risky than Ashford. It trades about 0.13 of its potential returns per unit of risk. Ashford is currently generating about 0.04 of returns per unit of risk over similar time horizon. If you would invest 467.00 in Ashford on September 2, 2024 and sell it today you would earn a total of 30.00 from holding Ashford or generate 6.42% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 64.52% |
| Values | Daily Returns |
Bank of America vs. Ashford
Performance |
| Timeline |
| Bank of America |
| Ashford |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
Bank of America and Ashford Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bank of America and Ashford
The main advantage of trading using opposite Bank of America and Ashford positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of America position performs unexpectedly, Ashford 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 Ashford will offset losses from the drop in Ashford's long position.| Bank of America vs. Citigroup | Bank of America vs. Nu Holdings | Bank of America vs. HSBC Holdings PLC | Bank of America vs. Bank of Montreal |
| Ashford vs. Braemar Hotel Resorts | Ashford vs. Conifer Holding | Ashford vs. Citizens Community Bancorp | Ashford vs. AstroNova |
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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