Correlation Between Bank of America and Dow Jones
Can any of the company-specific risk be diversified away by investing in both Bank of America and Dow Jones 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 Dow Jones 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 Dow Jones Industrial, you can compare the effects of market volatilities on Bank of America and Dow Jones 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 Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of America and Dow Jones.
Diversification Opportunities for Bank of America and Dow Jones
0.29 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Bank and Dow is 0.29. Overlapping area represents the amount of risk that can be diversified away by holding Bank of America and Dow Jones Industrial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dow Jones Industrial 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 Dow Jones. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dow Jones Industrial has no effect on the direction of Bank of America i.e., Bank of America and Dow Jones go up and down completely randomly.
Pair Corralation between Bank of America and Dow Jones
Assuming the 90 days horizon Bank of America is expected to generate 1.89 times more return on investment than Dow Jones. However, Bank of America is 1.89 times more volatile than Dow Jones Industrial. It trades about 0.31 of its potential returns per unit of risk. Dow Jones Industrial is currently generating about 0.33 per unit of risk. If you would invest 4,401 in Bank of America on November 9, 2024 and sell it today you would earn a total of 208.00 from holding Bank of America or generate 4.73% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 55.0% |
| Values | Daily Returns |
Bank of America vs. Dow Jones Industrial
Performance |
| Timeline |
Bank of America and Dow Jones Volatility Contrast
Predicted Return Density |
| Returns |
Bank of America
Pair trading matchups for Bank of America
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with Bank of America and Dow Jones
The main advantage of trading using opposite Bank of America and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of America position performs unexpectedly, Dow Jones 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 Dow Jones will offset losses from the drop in Dow Jones' long position.| Bank of America vs. COMPUTER MODELLING | Bank of America vs. VARIOUS EATERIES LS | Bank of America vs. VIRGIN WINES UK | Bank of America vs. ITALIAN WINE BRANDS |
| Dow Jones vs. Douglas Emmett | Dow Jones vs. Todos Medical | Dow Jones vs. Eastern Co | Dow Jones vs. Merit Medical Systems |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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