Correlation Between Marsh McLennan and Zhibao Technology
Can any of the company-specific risk be diversified away by investing in both Marsh McLennan and Zhibao Technology 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 Marsh McLennan and Zhibao Technology into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Marsh McLennan Companies and Zhibao Technology Class, you can compare the effects of market volatilities on Marsh McLennan and Zhibao Technology 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 Marsh McLennan with a short position of Zhibao Technology. Check out your portfolio center. Please also check ongoing floating volatility patterns of Marsh McLennan and Zhibao Technology.
Diversification Opportunities for Marsh McLennan and Zhibao Technology
0.59 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Marsh and Zhibao is 0.59. Overlapping area represents the amount of risk that can be diversified away by holding Marsh McLennan Companies and Zhibao Technology Class in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Zhibao Technology Class and Marsh McLennan 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 Marsh McLennan Companies are associated (or correlated) with Zhibao Technology. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Zhibao Technology Class has no effect on the direction of Marsh McLennan i.e., Marsh McLennan and Zhibao Technology go up and down completely randomly.
Pair Corralation between Marsh McLennan and Zhibao Technology
Considering the 90-day investment horizon Marsh McLennan Companies is expected to generate 0.15 times more return on investment than Zhibao Technology. However, Marsh McLennan Companies is 6.73 times less risky than Zhibao Technology. It trades about -0.06 of its potential returns per unit of risk. Zhibao Technology Class is currently generating about -0.19 per unit of risk. If you would invest 21,978 in Marsh McLennan Companies on October 6, 2024 and sell it today you would lose (851.00) from holding Marsh McLennan Companies or give up 3.87% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Marsh McLennan Companies vs. Zhibao Technology Class
Performance |
Timeline |
Marsh McLennan Companies |
Zhibao Technology Class |
Marsh McLennan and Zhibao Technology Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Marsh McLennan and Zhibao Technology
The main advantage of trading using opposite Marsh McLennan and Zhibao Technology positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Marsh McLennan position performs unexpectedly, Zhibao Technology 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 Zhibao Technology will offset losses from the drop in Zhibao Technology's long position.Marsh McLennan vs. Arthur J Gallagher | Marsh McLennan vs. Willis Towers Watson | Marsh McLennan vs. Brown Brown | Marsh McLennan vs. Erie Indemnity |
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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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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