Correlation Between Alibaba Group and Zhaojin Mining
Can any of the company-specific risk be diversified away by investing in both Alibaba Group and Zhaojin Mining 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 Alibaba Group and Zhaojin Mining into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Alibaba Group Holding and Zhaojin Mining Industry, you can compare the effects of market volatilities on Alibaba Group and Zhaojin Mining 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 Alibaba Group with a short position of Zhaojin Mining. Check out your portfolio center. Please also check ongoing floating volatility patterns of Alibaba Group and Zhaojin Mining.
Diversification Opportunities for Alibaba Group and Zhaojin Mining
0.63 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Alibaba and Zhaojin is 0.63. Overlapping area represents the amount of risk that can be diversified away by holding Alibaba Group Holding and Zhaojin Mining Industry in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Zhaojin Mining Industry and Alibaba Group 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 Alibaba Group Holding are associated (or correlated) with Zhaojin Mining. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Zhaojin Mining Industry has no effect on the direction of Alibaba Group i.e., Alibaba Group and Zhaojin Mining go up and down completely randomly.
Pair Corralation between Alibaba Group and Zhaojin Mining
Given the investment horizon of 90 days Alibaba Group is expected to generate 3.67 times less return on investment than Zhaojin Mining. But when comparing it to its historical volatility, Alibaba Group Holding is 1.43 times less risky than Zhaojin Mining. It trades about 0.02 of its potential returns per unit of risk. Zhaojin Mining Industry is currently generating about 0.04 of returns per unit of risk over similar time horizon. If you would invest 110.00 in Zhaojin Mining Industry on October 22, 2024 and sell it today you would earn a total of 42.00 from holding Zhaojin Mining Industry or generate 38.18% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 98.74% |
Values | Daily Returns |
Alibaba Group Holding vs. Zhaojin Mining Industry
Performance |
Timeline |
Alibaba Group Holding |
Zhaojin Mining Industry |
Alibaba Group and Zhaojin Mining Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Alibaba Group and Zhaojin Mining
The main advantage of trading using opposite Alibaba Group and Zhaojin Mining positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Alibaba Group position performs unexpectedly, Zhaojin Mining 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 Zhaojin Mining will offset losses from the drop in Zhaojin Mining's long position.Alibaba Group vs. PDD Holdings | Alibaba Group vs. MercadoLibre | Alibaba Group vs. JD Inc Adr | Alibaba Group vs. Sea |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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