Correlation Between Alibaba Group and JB Hunt
Can any of the company-specific risk be diversified away by investing in both Alibaba Group and JB Hunt 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 JB Hunt 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 JB Hunt Transport, you can compare the effects of market volatilities on Alibaba Group and JB Hunt 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 JB Hunt. Check out your portfolio center. Please also check ongoing floating volatility patterns of Alibaba Group and JB Hunt.
Diversification Opportunities for Alibaba Group and JB Hunt
-0.83 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Alibaba and J1BH34 is -0.83. Overlapping area represents the amount of risk that can be diversified away by holding Alibaba Group Holding and JB Hunt Transport in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on JB Hunt Transport 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 JB Hunt. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of JB Hunt Transport has no effect on the direction of Alibaba Group i.e., Alibaba Group and JB Hunt go up and down completely randomly.
Pair Corralation between Alibaba Group and JB Hunt
Assuming the 90 days trading horizon Alibaba Group Holding is expected to generate 1.71 times more return on investment than JB Hunt. However, Alibaba Group is 1.71 times more volatile than JB Hunt Transport. It trades about 0.07 of its potential returns per unit of risk. JB Hunt Transport is currently generating about 0.04 per unit of risk. If you would invest 1,284 in Alibaba Group Holding on October 26, 2024 and sell it today you would earn a total of 536.00 from holding Alibaba Group Holding or generate 41.74% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Significant |
| Accuracy | 99.26% |
| Values | Daily Returns |
Alibaba Group Holding vs. JB Hunt Transport
Performance |
| Timeline |
| Alibaba Group Holding |
| JB Hunt Transport |
Alibaba Group and JB Hunt Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Alibaba Group and JB Hunt
The main advantage of trading using opposite Alibaba Group and JB Hunt positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Alibaba Group position performs unexpectedly, JB Hunt 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 JB Hunt will offset losses from the drop in JB Hunt's long position.| Alibaba Group vs. Zoom Video Communications | Alibaba Group vs. CVS Health | Alibaba Group vs. Warner Music Group | Alibaba Group vs. Autohome |
| JB Hunt vs. Take Two Interactive Software | JB Hunt vs. Fidelity National Information | JB Hunt vs. Clover Health Investments, | JB Hunt vs. DENTSPLY SIRONA |
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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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