Correlation Between Aston Martin and Volkswagen
Can any of the company-specific risk be diversified away by investing in both Aston Martin and Volkswagen 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 Volkswagen 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 Volkswagen AG VZO, you can compare the effects of market volatilities on Aston Martin and Volkswagen 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 Volkswagen. Check out your portfolio center. Please also check ongoing floating volatility patterns of Aston Martin and Volkswagen.
Diversification Opportunities for Aston Martin and Volkswagen
-0.07 | Correlation Coefficient |
Good diversification
The 3 months correlation between Aston and Volkswagen is -0.07. Overlapping area represents the amount of risk that can be diversified away by holding Aston Martin Lagonda and Volkswagen AG VZO in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Volkswagen AG VZO 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 Volkswagen. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Volkswagen AG VZO has no effect on the direction of Aston Martin i.e., Aston Martin and Volkswagen go up and down completely randomly.
Pair Corralation between Aston Martin and Volkswagen
Assuming the 90 days horizon Aston Martin Lagonda is expected to under-perform the Volkswagen. In addition to that, Aston Martin is 1.3 times more volatile than Volkswagen AG VZO. It trades about -0.01 of its total potential returns per unit of risk. Volkswagen AG VZO is currently generating about 0.01 per unit of volatility. If you would invest 10,377 in Volkswagen AG VZO on November 2, 2024 and sell it today you would lose (522.00) from holding Volkswagen AG VZO or give up 5.03% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 99.19% |
| Values | Daily Returns |
Aston Martin Lagonda vs. Volkswagen AG VZO
Performance |
| Timeline |
| Aston Martin Lagonda |
| Volkswagen AG VZO |
Aston Martin and Volkswagen Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Aston Martin and Volkswagen
The main advantage of trading using opposite Aston Martin and Volkswagen positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Aston Martin position performs unexpectedly, Volkswagen 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 Volkswagen will offset losses from the drop in Volkswagen's long position.| Aston Martin vs. Geely Automobile Holdings | Aston Martin vs. Guangzhou Automobile Group | Aston Martin vs. Dowlais Group plc | Aston Martin vs. NFI Group |
| Volkswagen vs. Volkswagen AG Pref | Volkswagen vs. Mercedes Benz Group AG | Volkswagen vs. Bayerische Motoren Werke | Volkswagen vs. Honda Motor Co |
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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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