Correlation Between MUTUIONLINE and LIFENET INSURANCE
Can any of the company-specific risk be diversified away by investing in both MUTUIONLINE and LIFENET INSURANCE 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 MUTUIONLINE and LIFENET INSURANCE into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between MUTUIONLINE and LIFENET INSURANCE CO, you can compare the effects of market volatilities on MUTUIONLINE and LIFENET INSURANCE 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 MUTUIONLINE with a short position of LIFENET INSURANCE. Check out your portfolio center. Please also check ongoing floating volatility patterns of MUTUIONLINE and LIFENET INSURANCE.
Diversification Opportunities for MUTUIONLINE and LIFENET INSURANCE
0.46 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between MUTUIONLINE and LIFENET is 0.46. Overlapping area represents the amount of risk that can be diversified away by holding MUTUIONLINE and LIFENET INSURANCE CO in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on LIFENET INSURANCE and MUTUIONLINE 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 MUTUIONLINE are associated (or correlated) with LIFENET INSURANCE. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of LIFENET INSURANCE has no effect on the direction of MUTUIONLINE i.e., MUTUIONLINE and LIFENET INSURANCE go up and down completely randomly.
Pair Corralation between MUTUIONLINE and LIFENET INSURANCE
Assuming the 90 days trading horizon MUTUIONLINE is expected to generate 0.75 times more return on investment than LIFENET INSURANCE. However, MUTUIONLINE is 1.33 times less risky than LIFENET INSURANCE. It trades about 0.05 of its potential returns per unit of risk. LIFENET INSURANCE CO is currently generating about 0.04 per unit of risk. If you would invest 2,454 in MUTUIONLINE on August 29, 2024 and sell it today you would earn a total of 1,351 from holding MUTUIONLINE or generate 55.05% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
MUTUIONLINE vs. LIFENET INSURANCE CO
Performance |
Timeline |
MUTUIONLINE |
LIFENET INSURANCE |
MUTUIONLINE and LIFENET INSURANCE Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with MUTUIONLINE and LIFENET INSURANCE
The main advantage of trading using opposite MUTUIONLINE and LIFENET INSURANCE positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if MUTUIONLINE position performs unexpectedly, LIFENET INSURANCE 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 LIFENET INSURANCE will offset losses from the drop in LIFENET INSURANCE's long position.MUTUIONLINE vs. Apple Inc | MUTUIONLINE vs. Apple Inc | MUTUIONLINE vs. Superior Plus Corp | MUTUIONLINE vs. SIVERS SEMICONDUCTORS AB |
LIFENET INSURANCE vs. Xtrackers LevDAX | LIFENET INSURANCE vs. Xtrackers ShortDAX | LIFENET INSURANCE vs. Lyxor 1 |
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 Suggestion module to get suggestions outside of your existing asset allocation including your own model portfolios.
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