Correlation Between GSR II and CAVA Group,
Can any of the company-specific risk be diversified away by investing in both GSR II and CAVA Group, 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 GSR II and CAVA Group, into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between GSR II Meteora and CAVA Group,, you can compare the effects of market volatilities on GSR II and CAVA Group, 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 GSR II with a short position of CAVA Group,. Check out your portfolio center. Please also check ongoing floating volatility patterns of GSR II and CAVA Group,.
Diversification Opportunities for GSR II and CAVA Group,
-0.31 | Correlation Coefficient |
Very good diversification
The 3 months correlation between GSR and CAVA is -0.31. Overlapping area represents the amount of risk that can be diversified away by holding GSR II Meteora and CAVA Group, in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CAVA Group, and GSR II 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 GSR II Meteora are associated (or correlated) with CAVA Group,. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CAVA Group, has no effect on the direction of GSR II i.e., GSR II and CAVA Group, go up and down completely randomly.
Pair Corralation between GSR II and CAVA Group,
Assuming the 90 days horizon GSR II Meteora is expected to under-perform the CAVA Group,. But the stock apears to be less risky and, when comparing its historical volatility, GSR II Meteora is 11.27 times less risky than CAVA Group,. The stock trades about -0.12 of its potential returns per unit of risk. The CAVA Group, is currently generating about 0.06 of returns per unit of risk over similar time horizon. If you would invest 0.00 in CAVA Group, on September 4, 2024 and sell it today you would earn a total of 14,184 from holding CAVA Group, or generate 9.223372036854776E16% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 36.93% |
| Values | Daily Returns |
GSR II Meteora vs. CAVA Group,
Performance |
| Timeline |
| GSR II Meteora |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
| CAVA Group, |
GSR II and CAVA Group, Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with GSR II and CAVA Group,
The main advantage of trading using opposite GSR II and CAVA Group, positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GSR II position performs unexpectedly, CAVA Group, 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 CAVA Group, will offset losses from the drop in CAVA Group,'s long position.| GSR II vs. CAVA Group, | GSR II vs. Dominos Pizza | GSR II vs. Dave Busters Entertainment | GSR II vs. RCI Hospitality Holdings |
| CAVA Group, vs. Tencent Music Entertainment | CAVA Group, vs. Asbury Automotive Group | CAVA Group, vs. Stagwell | CAVA Group, vs. Fluent Inc |
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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