Correlation Between Asbury Automotive and Verde Clean
Can any of the company-specific risk be diversified away by investing in both Asbury Automotive and Verde Clean 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 Asbury Automotive and Verde Clean into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Asbury Automotive Group and Verde Clean Fuels, you can compare the effects of market volatilities on Asbury Automotive and Verde Clean 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 Asbury Automotive with a short position of Verde Clean. Check out your portfolio center. Please also check ongoing floating volatility patterns of Asbury Automotive and Verde Clean.
Diversification Opportunities for Asbury Automotive and Verde Clean
0.01 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Asbury and Verde is 0.01. Overlapping area represents the amount of risk that can be diversified away by holding Asbury Automotive Group and Verde Clean Fuels in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Verde Clean Fuels and Asbury Automotive 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 Asbury Automotive Group are associated (or correlated) with Verde Clean. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Verde Clean Fuels has no effect on the direction of Asbury Automotive i.e., Asbury Automotive and Verde Clean go up and down completely randomly.
Pair Corralation between Asbury Automotive and Verde Clean
Considering the 90-day investment horizon Asbury Automotive Group is expected to generate 0.37 times more return on investment than Verde Clean. However, Asbury Automotive Group is 2.73 times less risky than Verde Clean. It trades about 0.03 of its potential returns per unit of risk. Verde Clean Fuels is currently generating about 0.01 per unit of risk. If you would invest 19,929 in Asbury Automotive Group on December 4, 2024 and sell it today you would earn a total of 5,335 from holding Asbury Automotive Group or generate 26.77% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Asbury Automotive Group vs. Verde Clean Fuels
Performance |
Timeline |
Asbury Automotive |
Verde Clean Fuels |
Asbury Automotive and Verde Clean Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Asbury Automotive and Verde Clean
The main advantage of trading using opposite Asbury Automotive and Verde Clean positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Asbury Automotive position performs unexpectedly, Verde Clean 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 Verde Clean will offset losses from the drop in Verde Clean's long position.Asbury Automotive vs. Sonic Automotive | Asbury Automotive vs. Lithia Motors | Asbury Automotive vs. AutoNation | Asbury Automotive vs. Penske Automotive Group |
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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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