Correlation Between Asbury Automotive and Patterson UTI
Can any of the company-specific risk be diversified away by investing in both Asbury Automotive and Patterson UTI 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 Patterson UTI 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 Patterson UTI Energy, you can compare the effects of market volatilities on Asbury Automotive and Patterson UTI 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 Patterson UTI. Check out your portfolio center. Please also check ongoing floating volatility patterns of Asbury Automotive and Patterson UTI.
Diversification Opportunities for Asbury Automotive and Patterson UTI
0.32 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Asbury and Patterson is 0.32. Overlapping area represents the amount of risk that can be diversified away by holding Asbury Automotive Group and Patterson UTI Energy in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Patterson UTI Energy 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 Patterson UTI. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Patterson UTI Energy has no effect on the direction of Asbury Automotive i.e., Asbury Automotive and Patterson UTI go up and down completely randomly.
Pair Corralation between Asbury Automotive and Patterson UTI
Considering the 90-day investment horizon Asbury Automotive Group is expected to generate 0.7 times more return on investment than Patterson UTI. However, Asbury Automotive Group is 1.42 times less risky than Patterson UTI. It trades about 0.35 of its potential returns per unit of risk. Patterson UTI Energy is currently generating about 0.13 per unit of risk. If you would invest 22,558 in Asbury Automotive Group on August 28, 2024 and sell it today you would earn a total of 4,124 from holding Asbury Automotive Group or generate 18.28% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Asbury Automotive Group vs. Patterson UTI Energy
Performance |
Timeline |
Asbury Automotive |
Patterson UTI Energy |
Asbury Automotive and Patterson UTI Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Asbury Automotive and Patterson UTI
The main advantage of trading using opposite Asbury Automotive and Patterson UTI positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Asbury Automotive position performs unexpectedly, Patterson UTI 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 Patterson UTI will offset losses from the drop in Patterson UTI's long position.Asbury Automotive vs. Kingsway Financial Services | Asbury Automotive vs. KAR Auction Services | Asbury Automotive vs. Cango Inc | Asbury Automotive vs. Vroom Inc |
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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 Portfolio Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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