Correlation Between Emerge Commerce and Alibaba Group
Can any of the company-specific risk be diversified away by investing in both Emerge Commerce 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 Emerge Commerce and Alibaba Group into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Emerge Commerce and Alibaba Group Holding, you can compare the effects of market volatilities on Emerge Commerce 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 Emerge Commerce with a short position of Alibaba Group. Check out your portfolio center. Please also check ongoing floating volatility patterns of Emerge Commerce and Alibaba Group.
Diversification Opportunities for Emerge Commerce and Alibaba Group
-0.1 | Correlation Coefficient |
Good diversification
The 3 months correlation between Emerge and Alibaba is -0.1. Overlapping area represents the amount of risk that can be diversified away by holding Emerge Commerce 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 Emerge Commerce 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 Emerge Commerce 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 Emerge Commerce i.e., Emerge Commerce and Alibaba Group go up and down completely randomly.
Pair Corralation between Emerge Commerce and Alibaba Group
Assuming the 90 days horizon Emerge Commerce is expected to generate 13.01 times more return on investment than Alibaba Group. However, Emerge Commerce is 13.01 times more volatile than Alibaba Group Holding. It trades about 0.04 of its potential returns per unit of risk. Alibaba Group Holding is currently generating about 0.0 per unit of risk. If you would invest 13.00 in Emerge Commerce on October 3, 2024 and sell it today you would lose (10.49) from holding Emerge Commerce or give up 80.69% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Emerge Commerce vs. Alibaba Group Holding
Performance |
Timeline |
Emerge Commerce |
Alibaba Group Holding |
Emerge Commerce and Alibaba Group Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Emerge Commerce and Alibaba Group
The main advantage of trading using opposite Emerge Commerce and Alibaba Group positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Emerge Commerce 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.Emerge Commerce vs. Allegroeu SA | Emerge Commerce vs. ZALANDO SE ADR | Emerge Commerce vs. AKA Brands Holding | Emerge Commerce vs. ASOS plc PK |
Alibaba Group vs. Meituan ADR | Alibaba Group vs. Meituan | Alibaba Group vs. Qurate Retail Series | Alibaba Group vs. ThredUp |
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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