Correlation Between Bank of America and Doosan Fuel
Can any of the company-specific risk be diversified away by investing in both Bank of America and Doosan Fuel 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 Doosan Fuel 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 Doosan Fuel Cell, you can compare the effects of market volatilities on Bank of America and Doosan Fuel 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 Doosan Fuel. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of America and Doosan Fuel.
Diversification Opportunities for Bank of America and Doosan Fuel
-0.67 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Bank and Doosan is -0.67. Overlapping area represents the amount of risk that can be diversified away by holding Bank of America and Doosan Fuel Cell in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Doosan Fuel Cell 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 Doosan Fuel. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Doosan Fuel Cell has no effect on the direction of Bank of America i.e., Bank of America and Doosan Fuel go up and down completely randomly.
Pair Corralation between Bank of America and Doosan Fuel
Considering the 90-day investment horizon Bank of America is expected to generate 0.5 times more return on investment than Doosan Fuel. However, Bank of America is 2.02 times less risky than Doosan Fuel. It trades about 0.1 of its potential returns per unit of risk. Doosan Fuel Cell is currently generating about -0.06 per unit of risk. If you would invest 3,938 in Bank of America on September 1, 2024 and sell it today you would earn a total of 813.00 from holding Bank of America or generate 20.64% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 96.83% |
| Values | Daily Returns |
Bank of America vs. Doosan Fuel Cell
Performance |
| Timeline |
| Bank of America |
| Doosan Fuel Cell |
Bank of America and Doosan Fuel Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bank of America and Doosan Fuel
The main advantage of trading using opposite Bank of America and Doosan Fuel positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of America position performs unexpectedly, Doosan Fuel 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 Doosan Fuel will offset losses from the drop in Doosan Fuel'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 |
| Doosan Fuel vs. LS Electric | Doosan Fuel vs. KB Financial Group | Doosan Fuel vs. Dongbang Ship Machinery |
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 Portfolio Analyzer module to portfolio analysis module that provides access to portfolio diagnostics and optimization engine.
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