Correlation Between OReilly Automotive and AutoNation
Can any of the company-specific risk be diversified away by investing in both OReilly Automotive and AutoNation 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 OReilly Automotive and AutoNation into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between OReilly Automotive and AutoNation, you can compare the effects of market volatilities on OReilly Automotive and AutoNation 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 OReilly Automotive with a short position of AutoNation. Check out your portfolio center. Please also check ongoing floating volatility patterns of OReilly Automotive and AutoNation.
Diversification Opportunities for OReilly Automotive and AutoNation
0.7 | Correlation Coefficient |
Poor diversification
The 3 months correlation between OReilly and AutoNation is 0.7. Overlapping area represents the amount of risk that can be diversified away by holding OReilly Automotive and AutoNation in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on AutoNation and OReilly 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 OReilly Automotive are associated (or correlated) with AutoNation. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of AutoNation has no effect on the direction of OReilly Automotive i.e., OReilly Automotive and AutoNation go up and down completely randomly.
Pair Corralation between OReilly Automotive and AutoNation
Given the investment horizon of 90 days OReilly Automotive is expected to generate 0.69 times more return on investment than AutoNation. However, OReilly Automotive is 1.45 times less risky than AutoNation. It trades about 0.17 of its potential returns per unit of risk. AutoNation is currently generating about -0.17 per unit of risk. If you would invest 131,606 in OReilly Automotive on December 4, 2024 and sell it today you would earn a total of 5,347 from holding OReilly Automotive or generate 4.06% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 95.24% |
| Values | Daily Returns |
OReilly Automotive vs. AutoNation
Performance |
| Timeline |
| OReilly Automotive |
| AutoNation |
OReilly Automotive and AutoNation Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with OReilly Automotive and AutoNation
The main advantage of trading using opposite OReilly Automotive and AutoNation positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if OReilly Automotive position performs unexpectedly, AutoNation 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 AutoNation will offset losses from the drop in AutoNation's long position.| OReilly Automotive vs. Dicks Sporting Goods | OReilly Automotive vs. Ulta Beauty | OReilly Automotive vs. Williams Sonoma | OReilly Automotive vs. RH |
| AutoNation vs. Sonic Automotive | AutoNation vs. Lithia Motors | AutoNation vs. Asbury Automotive Group | AutoNation vs. Penske Automotive Group |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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