Correlation Between Sea and Alibaba Group
Can any of the company-specific risk be diversified away by investing in both Sea and Alibaba Group 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 Sea and Alibaba Group into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sea and Alibaba Group Holding, you can compare the effects of market volatilities on Sea and Alibaba Group 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 Sea with a short position of Alibaba Group. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sea and Alibaba Group.
Diversification Opportunities for Sea and Alibaba Group
0.34 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Sea and Alibaba is 0.34. Overlapping area represents the amount of risk that can be diversified away by holding Sea and Alibaba Group Holding in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Alibaba Group Holding and Sea 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 Sea are associated (or correlated) with Alibaba Group. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Alibaba Group Holding has no effect on the direction of Sea i.e., Sea and Alibaba Group go up and down completely randomly.
Pair Corralation between Sea and Alibaba Group
Allowing for the 90-day total investment horizon Sea is expected to generate 0.81 times more return on investment than Alibaba Group. However, Sea is 1.23 times less risky than Alibaba Group. It trades about 0.28 of its potential returns per unit of risk. Alibaba Group Holding is currently generating about 0.04 per unit of risk. If you would invest 7,831 in Sea on August 30, 2024 and sell it today you would earn a total of 3,740 from holding Sea or generate 47.76% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Sea vs. Alibaba Group Holding
Performance |
Timeline |
Sea |
Alibaba Group Holding |
Sea and Alibaba Group Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Sea and Alibaba Group
The main advantage of trading using opposite Sea and Alibaba Group positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sea position performs unexpectedly, Alibaba Group 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 Alibaba Group will offset losses from the drop in Alibaba Group's long position.The idea behind Sea and Alibaba Group Holding pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.Alibaba Group vs. PDD Holdings | Alibaba Group vs. MercadoLibre | Alibaba Group vs. JD Inc Adr | Alibaba Group vs. Sea |
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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