Correlation Between Cheche Group and GEN Restaurant
Can any of the company-specific risk be diversified away by investing in both Cheche Group and GEN Restaurant 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 Cheche Group and GEN Restaurant into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Cheche Group Class and GEN Restaurant Group,, you can compare the effects of market volatilities on Cheche Group and GEN Restaurant 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 Cheche Group with a short position of GEN Restaurant. Check out your portfolio center. Please also check ongoing floating volatility patterns of Cheche Group and GEN Restaurant.
Diversification Opportunities for Cheche Group and GEN Restaurant
0.33 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Cheche and GEN is 0.33. Overlapping area represents the amount of risk that can be diversified away by holding Cheche Group Class and GEN Restaurant Group, in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on GEN Restaurant Group, and Cheche Group 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 Cheche Group Class are associated (or correlated) with GEN Restaurant. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of GEN Restaurant Group, has no effect on the direction of Cheche Group i.e., Cheche Group and GEN Restaurant go up and down completely randomly.
Pair Corralation between Cheche Group and GEN Restaurant
Considering the 90-day investment horizon Cheche Group is expected to generate 4.43 times less return on investment than GEN Restaurant. But when comparing it to its historical volatility, Cheche Group Class is 1.85 times less risky than GEN Restaurant. It trades about 0.02 of its potential returns per unit of risk. GEN Restaurant Group, is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 0.00 in GEN Restaurant Group, on September 2, 2024 and sell it today you would earn a total of 848.00 from holding GEN Restaurant Group, or generate 9.223372036854776E16% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 81.17% |
| Values | Daily Returns |
Cheche Group Class vs. GEN Restaurant Group,
Performance |
| Timeline |
| Cheche Group Class |
| GEN Restaurant Group, |
Cheche Group and GEN Restaurant Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Cheche Group and GEN Restaurant
The main advantage of trading using opposite Cheche Group and GEN Restaurant positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Cheche Group position performs unexpectedly, GEN Restaurant 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 GEN Restaurant will offset losses from the drop in GEN Restaurant's long position.| Cheche Group vs. PennantPark Floating Rate | Cheche Group vs. Arrow Electronics | Cheche Group vs. Summit Hotel Properties | Cheche Group vs. Morgan Stanley |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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