Correlation Between Xponential Fitness and Codexis
Can any of the company-specific risk be diversified away by investing in both Xponential Fitness and Codexis 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 Codexis into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Xponential Fitness and Codexis, you can compare the effects of market volatilities on Xponential Fitness and Codexis 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 Codexis. Check out your portfolio center. Please also check ongoing floating volatility patterns of Xponential Fitness and Codexis.
Diversification Opportunities for Xponential Fitness and Codexis
0.88 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Xponential and Codexis is 0.88. Overlapping area represents the amount of risk that can be diversified away by holding Xponential Fitness and Codexis in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Codexis 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 Codexis. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Codexis has no effect on the direction of Xponential Fitness i.e., Xponential Fitness and Codexis go up and down completely randomly.
Pair Corralation between Xponential Fitness and Codexis
Given the investment horizon of 90 days Xponential Fitness is expected to generate 0.65 times more return on investment than Codexis. However, Xponential Fitness is 1.54 times less risky than Codexis. It trades about -0.17 of its potential returns per unit of risk. Codexis is currently generating about -0.13 per unit of risk. If you would invest 919.00 in Xponential Fitness on January 16, 2025 and sell it today you would lose (169.00) from holding Xponential Fitness or give up 18.39% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Xponential Fitness vs. Codexis
Performance |
| Timeline |
| Xponential Fitness |
| Codexis |
Xponential Fitness and Codexis Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Xponential Fitness and Codexis
The main advantage of trading using opposite Xponential Fitness and Codexis positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Xponential Fitness position performs unexpectedly, Codexis 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 Codexis will offset losses from the drop in Codexis' long position.| Xponential Fitness vs. Planet Fitness | Xponential Fitness vs. JAKKS Pacific | Xponential Fitness vs. Acushnet Holdings Corp | Xponential Fitness vs. OneSpaWorld Holdings |
| Codexis vs. Nuvation Bio | Codexis vs. Lyell Immunopharma | Codexis vs. Century Therapeutics | Codexis vs. Generation Bio Co |
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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