Correlation Between Xponential Fitness and Stratasys
Can any of the company-specific risk be diversified away by investing in both Xponential Fitness and Stratasys 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 Stratasys into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Xponential Fitness and Stratasys, you can compare the effects of market volatilities on Xponential Fitness and Stratasys 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 Stratasys. Check out your portfolio center. Please also check ongoing floating volatility patterns of Xponential Fitness and Stratasys.
Diversification Opportunities for Xponential Fitness and Stratasys
0.61 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Xponential and Stratasys is 0.61. Overlapping area represents the amount of risk that can be diversified away by holding Xponential Fitness and Stratasys in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Stratasys 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 Stratasys. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Stratasys has no effect on the direction of Xponential Fitness i.e., Xponential Fitness and Stratasys go up and down completely randomly.
Pair Corralation between Xponential Fitness and Stratasys
Given the investment horizon of 90 days Xponential Fitness is expected to generate 1.0 times less return on investment than Stratasys. In addition to that, Xponential Fitness is 1.13 times more volatile than Stratasys. It trades about 0.18 of its total potential returns per unit of risk. Stratasys is currently generating about 0.21 per unit of volatility. If you would invest 770.00 in Stratasys on August 27, 2024 and sell it today you would earn a total of 206.00 from holding Stratasys or generate 26.75% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Xponential Fitness vs. Stratasys
Performance |
| Timeline |
| Xponential Fitness |
| Stratasys |
Xponential Fitness and Stratasys Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Xponential Fitness and Stratasys
The main advantage of trading using opposite Xponential Fitness and Stratasys positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Xponential Fitness position performs unexpectedly, Stratasys 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 Stratasys will offset losses from the drop in Stratasys' long position.| Xponential Fitness vs. Planet Fitness | Xponential Fitness vs. Bowlero Corp | Xponential Fitness vs. JAKKS Pacific | Xponential Fitness vs. Acushnet Holdings Corp |
| Stratasys vs. D Wave Quantum | Stratasys vs. Rigetti Computing | Stratasys vs. Cricut Inc | Stratasys vs. Quantum Computing |
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 Optimization module to compute new portfolio that will generate highest expected return given your specified tolerance for risk.
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