Correlation Between Bank of America and Hanwha Chemical
Can any of the company-specific risk be diversified away by investing in both Bank of America and Hanwha Chemical 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 Hanwha Chemical 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 Hanwha Chemical Corp, you can compare the effects of market volatilities on Bank of America and Hanwha Chemical 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 Hanwha Chemical. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of America and Hanwha Chemical.
Diversification Opportunities for Bank of America and Hanwha Chemical
-0.17 | Correlation Coefficient |
Good diversification
The 3 months correlation between Bank and Hanwha is -0.17. Overlapping area represents the amount of risk that can be diversified away by holding Bank of America and Hanwha Chemical Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hanwha Chemical Corp 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 Hanwha Chemical. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hanwha Chemical Corp has no effect on the direction of Bank of America i.e., Bank of America and Hanwha Chemical go up and down completely randomly.
Pair Corralation between Bank of America and Hanwha Chemical
Considering the 90-day investment horizon Bank of America is expected to generate 6.69 times less return on investment than Hanwha Chemical. But when comparing it to its historical volatility, Bank of America is 3.79 times less risky than Hanwha Chemical. It trades about 0.08 of its potential returns per unit of risk. Hanwha Chemical Corp is currently generating about 0.14 of returns per unit of risk over similar time horizon. If you would invest 1,794,000 in Hanwha Chemical Corp on November 6, 2024 and sell it today you would earn a total of 183,000 from holding Hanwha Chemical Corp or generate 10.2% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 89.47% |
| Values | Daily Returns |
Bank of America vs. Hanwha Chemical Corp
Performance |
| Timeline |
| Bank of America |
| Hanwha Chemical Corp |
Bank of America and Hanwha Chemical Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bank of America and Hanwha Chemical
The main advantage of trading using opposite Bank of America and Hanwha Chemical positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of America position performs unexpectedly, Hanwha Chemical 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 Hanwha Chemical will offset losses from the drop in Hanwha Chemical's long position.| Bank of America vs. Nu Holdings | Bank of America vs. HSBC Holdings PLC | Bank of America vs. Royal Bank of | Bank of America vs. Canadian Imperial Bank |
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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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