Correlation Between Xpeng and GreenPower
Can any of the company-specific risk be diversified away by investing in both Xpeng and GreenPower 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 Xpeng and GreenPower into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Xpeng Inc and GreenPower Motor, you can compare the effects of market volatilities on Xpeng and GreenPower 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 Xpeng with a short position of GreenPower. Check out your portfolio center. Please also check ongoing floating volatility patterns of Xpeng and GreenPower.
Diversification Opportunities for Xpeng and GreenPower
-0.88 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Xpeng and GreenPower is -0.88. Overlapping area represents the amount of risk that can be diversified away by holding Xpeng Inc and GreenPower Motor in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on GreenPower Motor and Xpeng 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 Xpeng Inc are associated (or correlated) with GreenPower. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of GreenPower Motor has no effect on the direction of Xpeng i.e., Xpeng and GreenPower go up and down completely randomly.
Pair Corralation between Xpeng and GreenPower
Given the investment horizon of 90 days Xpeng Inc is expected to generate 0.81 times more return on investment than GreenPower. However, Xpeng Inc is 1.23 times less risky than GreenPower. It trades about 0.2 of its potential returns per unit of risk. GreenPower Motor is currently generating about -0.05 per unit of risk. If you would invest 1,187 in Xpeng Inc on December 29, 2024 and sell it today you would earn a total of 783.00 from holding Xpeng Inc or generate 65.96% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Xpeng Inc vs. GreenPower Motor
Performance |
Timeline |
Xpeng Inc |
GreenPower Motor |
Xpeng and GreenPower Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Xpeng and GreenPower
The main advantage of trading using opposite Xpeng and GreenPower positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Xpeng position performs unexpectedly, GreenPower 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 GreenPower will offset losses from the drop in GreenPower's long position.The idea behind Xpeng Inc and GreenPower Motor 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.GreenPower vs. Phoenix Motor Common | GreenPower vs. Envirotech Vehicles | GreenPower vs. Volcon Inc | GreenPower vs. Zapp Electric Vehicles |
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 Correlation Analysis module to reduce portfolio risk simply by holding instruments which are not perfectly correlated.
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