Correlation Between Xponential Fitness and HUTCHMED DRC
Can any of the company-specific risk be diversified away by investing in both Xponential Fitness and HUTCHMED DRC 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 Xponential Fitness and HUTCHMED DRC into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Xponential Fitness and HUTCHMED DRC, you can compare the effects of market volatilities on Xponential Fitness and HUTCHMED DRC 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 Xponential Fitness with a short position of HUTCHMED DRC. Check out your portfolio center. Please also check ongoing floating volatility patterns of Xponential Fitness and HUTCHMED DRC.
Diversification Opportunities for Xponential Fitness and HUTCHMED DRC
-0.55 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Xponential and HUTCHMED is -0.55. Overlapping area represents the amount of risk that can be diversified away by holding Xponential Fitness and HUTCHMED DRC in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on HUTCHMED DRC and Xponential Fitness 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 Xponential Fitness are associated (or correlated) with HUTCHMED DRC. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of HUTCHMED DRC has no effect on the direction of Xponential Fitness i.e., Xponential Fitness and HUTCHMED DRC go up and down completely randomly.
Pair Corralation between Xponential Fitness and HUTCHMED DRC
Given the investment horizon of 90 days Xponential Fitness is expected to under-perform the HUTCHMED DRC. In addition to that, Xponential Fitness is 1.94 times more volatile than HUTCHMED DRC. It trades about -0.08 of its total potential returns per unit of risk. HUTCHMED DRC is currently generating about 0.04 per unit of volatility. If you would invest 1,436 in HUTCHMED DRC on December 30, 2024 and sell it today you would earn a total of 89.00 from holding HUTCHMED DRC or generate 6.2% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Xponential Fitness vs. HUTCHMED DRC
Performance |
Timeline |
Xponential Fitness |
HUTCHMED DRC |
Xponential Fitness and HUTCHMED DRC Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Xponential Fitness and HUTCHMED DRC
The main advantage of trading using opposite Xponential Fitness and HUTCHMED DRC positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Xponential Fitness position performs unexpectedly, HUTCHMED DRC 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 HUTCHMED DRC will offset losses from the drop in HUTCHMED DRC's long position.Xponential Fitness vs. Planet Fitness | Xponential Fitness vs. JAKKS Pacific | Xponential Fitness vs. Acushnet Holdings Corp | Xponential Fitness vs. OneSpaWorld Holdings |
HUTCHMED DRC vs. ANI Pharmaceuticals | HUTCHMED DRC vs. Phibro Animal Health | HUTCHMED DRC vs. Prestige Brand Holdings | HUTCHMED DRC vs. Pacira BioSciences, |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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