Correlation Between Mullen Automotive and Xpeng
Can any of the company-specific risk be diversified away by investing in both Mullen Automotive and Xpeng 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 Mullen Automotive and Xpeng into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mullen Automotive and Xpeng Inc, you can compare the effects of market volatilities on Mullen Automotive and Xpeng 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 Mullen Automotive with a short position of Xpeng. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mullen Automotive and Xpeng.
Diversification Opportunities for Mullen Automotive and Xpeng
-0.82 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Mullen and Xpeng is -0.82. Overlapping area represents the amount of risk that can be diversified away by holding Mullen Automotive and Xpeng Inc in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Xpeng Inc and Mullen Automotive 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 Mullen Automotive are associated (or correlated) with Xpeng. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Xpeng Inc has no effect on the direction of Mullen Automotive i.e., Mullen Automotive and Xpeng go up and down completely randomly.
Pair Corralation between Mullen Automotive and Xpeng
Given the investment horizon of 90 days Mullen Automotive is expected to under-perform the Xpeng. In addition to that, Mullen Automotive is 3.33 times more volatile than Xpeng Inc. It trades about -0.53 of its total potential returns per unit of risk. Xpeng Inc is currently generating about 0.2 per unit of volatility. If you would invest 1,187 in Xpeng Inc on December 28, 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 |
Mullen Automotive vs. Xpeng Inc
Performance |
Timeline |
Mullen Automotive |
Xpeng Inc |
Mullen Automotive and Xpeng Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mullen Automotive and Xpeng
The main advantage of trading using opposite Mullen Automotive and Xpeng positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mullen Automotive position performs unexpectedly, Xpeng 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 Xpeng will offset losses from the drop in Xpeng's long position.The idea behind Mullen Automotive and Xpeng Inc 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.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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