Correlation Between LIFENET INSURANCE and Bank of America
Can any of the company-specific risk be diversified away by investing in both LIFENET INSURANCE and Bank of America 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 LIFENET INSURANCE and Bank of America into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between LIFENET INSURANCE CO and Verizon Communications, you can compare the effects of market volatilities on LIFENET INSURANCE and Bank of America 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 LIFENET INSURANCE with a short position of Bank of America. Check out your portfolio center. Please also check ongoing floating volatility patterns of LIFENET INSURANCE and Bank of America.
Diversification Opportunities for LIFENET INSURANCE and Bank of America
-0.03 | Correlation Coefficient |
Good diversification
The 3 months correlation between LIFENET and Bank is -0.03. Overlapping area represents the amount of risk that can be diversified away by holding LIFENET INSURANCE CO and Verizon Communications in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Verizon Communications and LIFENET INSURANCE 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 LIFENET INSURANCE CO are associated (or correlated) with Bank of America. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Verizon Communications has no effect on the direction of LIFENET INSURANCE i.e., LIFENET INSURANCE and Bank of America go up and down completely randomly.
Pair Corralation between LIFENET INSURANCE and Bank of America
Assuming the 90 days horizon LIFENET INSURANCE CO is expected to generate 1.83 times more return on investment than Bank of America. However, LIFENET INSURANCE is 1.83 times more volatile than Verizon Communications. It trades about 0.04 of its potential returns per unit of risk. Verizon Communications is currently generating about 0.04 per unit of risk. If you would invest 885.00 in LIFENET INSURANCE CO on August 27, 2024 and sell it today you would earn a total of 325.00 from holding LIFENET INSURANCE CO or generate 36.72% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
LIFENET INSURANCE CO vs. Verizon Communications
Performance |
| Timeline |
| LIFENET INSURANCE |
| Verizon Communications |
LIFENET INSURANCE and Bank of America Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with LIFENET INSURANCE and Bank of America
The main advantage of trading using opposite LIFENET INSURANCE and Bank of America positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if LIFENET INSURANCE position performs unexpectedly, Bank of America 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 America will offset losses from the drop in Bank of America's long position.| LIFENET INSURANCE vs. Lyxor 1 | LIFENET INSURANCE vs. Xtrackers ShortDAX | LIFENET INSURANCE vs. Xtrackers LevDAX |
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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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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