Correlation Between MetLife Preferred and Bank of Hawaii
Can any of the company-specific risk be diversified away by investing in both MetLife Preferred and Bank of Hawaii 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 MetLife Preferred and Bank of Hawaii into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between MetLife Preferred Stock and Bank of Hawaii, you can compare the effects of market volatilities on MetLife Preferred and Bank of Hawaii 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 MetLife Preferred with a short position of Bank of Hawaii. Check out your portfolio center. Please also check ongoing floating volatility patterns of MetLife Preferred and Bank of Hawaii.
Diversification Opportunities for MetLife Preferred and Bank of Hawaii
0.84 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between MetLife and Bank is 0.84. Overlapping area represents the amount of risk that can be diversified away by holding MetLife Preferred Stock and Bank of Hawaii in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bank of Hawaii and MetLife Preferred 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 MetLife Preferred Stock are associated (or correlated) with Bank of Hawaii. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bank of Hawaii has no effect on the direction of MetLife Preferred i.e., MetLife Preferred and Bank of Hawaii go up and down completely randomly.
Pair Corralation between MetLife Preferred and Bank of Hawaii
Assuming the 90 days trading horizon MetLife Preferred is expected to generate 3.01 times less return on investment than Bank of Hawaii. But when comparing it to its historical volatility, MetLife Preferred Stock is 1.43 times less risky than Bank of Hawaii. It trades about 0.02 of its potential returns per unit of risk. Bank of Hawaii is currently generating about 0.04 of returns per unit of risk over similar time horizon. If you would invest 1,592 in Bank of Hawaii on September 1, 2024 and sell it today you would earn a total of 106.00 from holding Bank of Hawaii or generate 6.66% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
MetLife Preferred Stock vs. Bank of Hawaii
Performance |
Timeline |
MetLife Preferred Stock |
Bank of Hawaii |
MetLife Preferred and Bank of Hawaii Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with MetLife Preferred and Bank of Hawaii
The main advantage of trading using opposite MetLife Preferred and Bank of Hawaii positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if MetLife Preferred position performs unexpectedly, Bank of Hawaii 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 Bank of Hawaii will offset losses from the drop in Bank of Hawaii's long position.MetLife Preferred vs. MetLife Preferred Stock | MetLife Preferred vs. The Allstate | MetLife Preferred vs. The Allstate | MetLife Preferred vs. Wells Fargo |
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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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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