Correlation Between Macys and AutoNation
Can any of the company-specific risk be diversified away by investing in both Macys 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 Macys and AutoNation into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Macys Inc and AutoNation, you can compare the effects of market volatilities on Macys 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 Macys with a short position of AutoNation. Check out your portfolio center. Please also check ongoing floating volatility patterns of Macys and AutoNation.
Diversification Opportunities for Macys and AutoNation
0.48 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Macys and AutoNation is 0.48. Overlapping area represents the amount of risk that can be diversified away by holding Macys Inc and AutoNation in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on AutoNation and Macys 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 Macys Inc 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 Macys i.e., Macys and AutoNation go up and down completely randomly.
Pair Corralation between Macys and AutoNation
Taking into account the 90-day investment horizon Macys Inc is expected to under-perform the AutoNation. In addition to that, Macys is 1.38 times more volatile than AutoNation. It trades about -0.03 of its total potential returns per unit of risk. AutoNation is currently generating about 0.02 per unit of volatility. If you would invest 16,951 in AutoNation on September 13, 2024 and sell it today you would earn a total of 540.00 from holding AutoNation or generate 3.19% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Macys Inc vs. AutoNation
Performance |
Timeline |
Macys Inc |
AutoNation |
Macys and AutoNation Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Macys and AutoNation
The main advantage of trading using opposite Macys and AutoNation positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Macys 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.The idea behind Macys Inc and AutoNation pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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