Correlation Between Bank of America and Bitwise Ethereum
Can any of the company-specific risk be diversified away by investing in both Bank of America and Bitwise Ethereum 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 Bitwise Ethereum 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 Bitwise Ethereum ETF, you can compare the effects of market volatilities on Bank of America and Bitwise Ethereum 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 Bitwise Ethereum. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of America and Bitwise Ethereum.
Diversification Opportunities for Bank of America and Bitwise Ethereum
0.86 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Bank and Bitwise is 0.86. Overlapping area represents the amount of risk that can be diversified away by holding Bank of America and Bitwise Ethereum ETF in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bitwise Ethereum ETF 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 Bitwise Ethereum. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bitwise Ethereum ETF has no effect on the direction of Bank of America i.e., Bank of America and Bitwise Ethereum go up and down completely randomly.
Pair Corralation between Bank of America and Bitwise Ethereum
Considering the 90-day investment horizon Bank of America is expected to generate 0.33 times more return on investment than Bitwise Ethereum. However, Bank of America is 3.03 times less risky than Bitwise Ethereum. It trades about 0.13 of its potential returns per unit of risk. Bitwise Ethereum ETF is currently generating about 0.01 per unit of risk. If you would invest 3,036 in Bank of America on August 27, 2024 and sell it today you would earn a total of 1,664 from holding Bank of America or generate 54.81% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 35.89% |
| Values | Daily Returns |
Bank of America vs. Bitwise Ethereum ETF
Performance |
| Timeline |
| Bank of America |
| Bitwise Ethereum ETF |
Bank of America and Bitwise Ethereum Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bank of America and Bitwise Ethereum
The main advantage of trading using opposite Bank of America and Bitwise Ethereum positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of America position performs unexpectedly, Bitwise Ethereum 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 Bitwise Ethereum will offset losses from the drop in Bitwise Ethereum's long position.| Bank of America vs. Toronto Dominion Bank | Bank of America vs. Nu Holdings | Bank of America vs. HSBC Holdings PLC | Bank of America vs. Bank of Montreal |
| Bitwise Ethereum vs. ProShares Trust | Bitwise Ethereum vs. iShares Ethereum Trust | Bitwise Ethereum vs. ProShares Trust | Bitwise Ethereum vs. Grayscale Ethereum Trust |
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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