Correlation Between Planet Fitness and Meta Platforms
Can any of the company-specific risk be diversified away by investing in both Planet Fitness and Meta Platforms 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 Planet Fitness and Meta Platforms into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Planet Fitness and Meta Platforms, you can compare the effects of market volatilities on Planet Fitness and Meta Platforms 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 Planet Fitness with a short position of Meta Platforms. Check out your portfolio center. Please also check ongoing floating volatility patterns of Planet Fitness and Meta Platforms.
Diversification Opportunities for Planet Fitness and Meta Platforms
0.0 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Planet and Meta is 0.0. Overlapping area represents the amount of risk that can be diversified away by holding Planet Fitness and Meta Platforms in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Meta Platforms and Planet 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 Planet Fitness are associated (or correlated) with Meta Platforms. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Meta Platforms has no effect on the direction of Planet Fitness i.e., Planet Fitness and Meta Platforms go up and down completely randomly.
Pair Corralation between Planet Fitness and Meta Platforms
Assuming the 90 days trading horizon Planet Fitness is expected to generate 6.56 times more return on investment than Meta Platforms. However, Planet Fitness is 6.56 times more volatile than Meta Platforms. It trades about 0.05 of its potential returns per unit of risk. Meta Platforms is currently generating about 0.25 per unit of risk. If you would invest 3,984 in Planet Fitness on September 7, 2024 and sell it today you would earn a total of 0.00 from holding Planet Fitness or generate 0.0% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Flat |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Planet Fitness vs. Meta Platforms
Performance |
Timeline |
Planet Fitness |
Meta Platforms |
Planet Fitness and Meta Platforms Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Planet Fitness and Meta Platforms
The main advantage of trading using opposite Planet Fitness and Meta Platforms positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Planet Fitness position performs unexpectedly, Meta Platforms 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 Meta Platforms will offset losses from the drop in Meta Platforms' long position.Planet Fitness vs. T4F Entretenimento SA | Planet Fitness vs. Energisa SA | Planet Fitness vs. BTG Pactual Logstica | Planet Fitness vs. Companhia Habitasul de |
Meta Platforms vs. Costco Wholesale | Meta Platforms vs. United States Steel | Meta Platforms vs. Iron Mountain Incorporated | Meta Platforms vs. Hospital Mater Dei |
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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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