Correlation Between Sonic Automotive and Lithia Motors
Can any of the company-specific risk be diversified away by investing in both Sonic Automotive and Lithia Motors 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 Sonic Automotive and Lithia Motors into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sonic Automotive and Lithia Motors, you can compare the effects of market volatilities on Sonic Automotive and Lithia Motors 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 Sonic Automotive with a short position of Lithia Motors. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sonic Automotive and Lithia Motors.
Diversification Opportunities for Sonic Automotive and Lithia Motors
0.9 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Sonic and Lithia is 0.9. Overlapping area represents the amount of risk that can be diversified away by holding Sonic Automotive and Lithia Motors in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Lithia Motors and Sonic 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 Sonic Automotive are associated (or correlated) with Lithia Motors. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Lithia Motors has no effect on the direction of Sonic Automotive i.e., Sonic Automotive and Lithia Motors go up and down completely randomly.
Pair Corralation between Sonic Automotive and Lithia Motors
Considering the 90-day investment horizon Sonic Automotive is expected to generate 1.09 times more return on investment than Lithia Motors. However, Sonic Automotive is 1.09 times more volatile than Lithia Motors. It trades about 0.27 of its potential returns per unit of risk. Lithia Motors is currently generating about 0.02 per unit of risk. If you would invest 6,340 in Sonic Automotive on October 19, 2024 and sell it today you would earn a total of 491.00 from holding Sonic Automotive or generate 7.74% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Sonic Automotive vs. Lithia Motors
Performance |
Timeline |
Sonic Automotive |
Lithia Motors |
Sonic Automotive and Lithia Motors Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Sonic Automotive and Lithia Motors
The main advantage of trading using opposite Sonic Automotive and Lithia Motors positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sonic Automotive position performs unexpectedly, Lithia Motors 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 Lithia Motors will offset losses from the drop in Lithia Motors' long position.Sonic Automotive vs. Lithia Motors | Sonic Automotive vs. AutoNation | Sonic Automotive vs. Asbury Automotive Group | Sonic Automotive vs. Penske Automotive Group |
Lithia Motors vs. Sonic Automotive | Lithia Motors vs. AutoNation | Lithia Motors vs. Asbury Automotive Group | Lithia Motors 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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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