Correlation Between Bank of America and Airports
Can any of the company-specific risk be diversified away by investing in both Bank of America and Airports 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 Airports 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 Airports of Thailand, you can compare the effects of market volatilities on Bank of America and Airports 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 Airports. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of America and Airports.
Diversification Opportunities for Bank of America and Airports
-0.22 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Bank and Airports is -0.22. Overlapping area represents the amount of risk that can be diversified away by holding Bank of America and Airports of Thailand in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Airports of Thailand 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 Airports. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Airports of Thailand has no effect on the direction of Bank of America i.e., Bank of America and Airports go up and down completely randomly.
Pair Corralation between Bank of America and Airports
Considering the 90-day investment horizon Bank of America is expected to generate 2.95 times less return on investment than Airports. But when comparing it to its historical volatility, Bank of America is 5.84 times less risky than Airports. It trades about 0.06 of its potential returns per unit of risk. Airports of Thailand is currently generating about 0.03 of returns per unit of risk over similar time horizon. If you would invest 210.00 in Airports of Thailand on August 29, 2024 and sell it today you would lose (85.00) from holding Airports of Thailand or give up 40.48% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 91.92% |
| Values | Daily Returns |
Bank of America vs. Airports of Thailand
Performance |
| Timeline |
| Bank of America |
| Airports of Thailand |
Bank of America and Airports Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bank of America and Airports
The main advantage of trading using opposite Bank of America and Airports positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of America position performs unexpectedly, Airports 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 Airports will offset losses from the drop in Airports' long position.| Bank of America vs. Nu Holdings | Bank of America vs. HSBC Holdings PLC | Bank of America vs. Bank of Nova |
| Airports vs. Aeroports de Paris | Airports vs. Corporacion America Airports | Airports vs. Grupo Aeroportuario del | Airports vs. Grupo Aeroportuario del |
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 Sectors module to list of equity sectors categorizing publicly traded companies based on their primary business activities.
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