Correlation Between Planet Fitness and Ebro Foods
Can any of the company-specific risk be diversified away by investing in both Planet Fitness and Ebro Foods 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 Ebro Foods into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Planet Fitness Cl and Ebro Foods, you can compare the effects of market volatilities on Planet Fitness and Ebro Foods 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 Ebro Foods. Check out your portfolio center. Please also check ongoing floating volatility patterns of Planet Fitness and Ebro Foods.
Diversification Opportunities for Planet Fitness and Ebro Foods
-0.22 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Planet and Ebro is -0.22. Overlapping area represents the amount of risk that can be diversified away by holding Planet Fitness Cl and Ebro Foods in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ebro Foods 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 Cl are associated (or correlated) with Ebro Foods. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ebro Foods has no effect on the direction of Planet Fitness i.e., Planet Fitness and Ebro Foods go up and down completely randomly.
Pair Corralation between Planet Fitness and Ebro Foods
Assuming the 90 days trading horizon Planet Fitness Cl is expected to generate 4.83 times more return on investment than Ebro Foods. However, Planet Fitness is 4.83 times more volatile than Ebro Foods. It trades about 0.15 of its potential returns per unit of risk. Ebro Foods is currently generating about 0.02 per unit of risk. If you would invest 8,229 in Planet Fitness Cl on September 12, 2024 and sell it today you would earn a total of 1,873 from holding Planet Fitness Cl or generate 22.76% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 95.38% |
| Values | Daily Returns |
Planet Fitness Cl vs. Ebro Foods
Performance |
| Timeline |
| Planet Fitness Cl |
| Ebro Foods |
Planet Fitness and Ebro Foods Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Planet Fitness and Ebro Foods
The main advantage of trading using opposite Planet Fitness and Ebro Foods positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Planet Fitness position performs unexpectedly, Ebro Foods 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 Ebro Foods will offset losses from the drop in Ebro Foods' long position.| Planet Fitness vs. Bisichi Mining PLC | Planet Fitness vs. Endeavour Mining Corp | Planet Fitness vs. Liberty Media Corp | Planet Fitness vs. AcadeMedia AB |
| Ebro Foods vs. One Media iP | Ebro Foods vs. Catena Media PLC | Ebro Foods vs. Iron Mountain | Ebro Foods vs. Prosiebensat 1 Media |
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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