Correlation Between Aston Martin and Mercedes-Benz Group
Can any of the company-specific risk be diversified away by investing in both Aston Martin and Mercedes-Benz Group 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 Aston Martin and Mercedes-Benz Group into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Aston Martin Lagonda and Mercedes Benz Group AG, you can compare the effects of market volatilities on Aston Martin and Mercedes-Benz Group 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 Aston Martin with a short position of Mercedes-Benz Group. Check out your portfolio center. Please also check ongoing floating volatility patterns of Aston Martin and Mercedes-Benz Group.
Diversification Opportunities for Aston Martin and Mercedes-Benz Group
-0.49 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Aston and Mercedes-Benz is -0.49. Overlapping area represents the amount of risk that can be diversified away by holding Aston Martin Lagonda and Mercedes Benz Group AG in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mercedes Benz Group and Aston Martin 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 Aston Martin Lagonda are associated (or correlated) with Mercedes-Benz Group. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mercedes Benz Group has no effect on the direction of Aston Martin i.e., Aston Martin and Mercedes-Benz Group go up and down completely randomly.
Pair Corralation between Aston Martin and Mercedes-Benz Group
Assuming the 90 days horizon Aston Martin Lagonda is expected to under-perform the Mercedes-Benz Group. In addition to that, Aston Martin is 2.89 times more volatile than Mercedes Benz Group AG. It trades about -0.08 of its total potential returns per unit of risk. Mercedes Benz Group AG is currently generating about 0.08 per unit of volatility. If you would invest 1,389 in Mercedes Benz Group AG on December 29, 2024 and sell it today you would earn a total of 111.00 from holding Mercedes Benz Group AG or generate 7.99% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 98.39% |
Values | Daily Returns |
Aston Martin Lagonda vs. Mercedes Benz Group AG
Performance |
Timeline |
Aston Martin Lagonda |
Mercedes Benz Group |
Aston Martin and Mercedes-Benz Group Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Aston Martin and Mercedes-Benz Group
The main advantage of trading using opposite Aston Martin and Mercedes-Benz Group positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Aston Martin position performs unexpectedly, Mercedes-Benz Group 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 Mercedes-Benz Group will offset losses from the drop in Mercedes-Benz Group's long position.Aston Martin vs. Polestar Automotive Holding | Aston Martin vs. Geely Automobile Holdings | Aston Martin vs. Mercedes Benz Group AG | Aston Martin vs. Porsche Automobile Holding |
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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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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