Correlation Between Polestar Automotive and Aston Martin
Can any of the company-specific risk be diversified away by investing in both Polestar Automotive and Aston Martin 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 Polestar Automotive and Aston Martin into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Polestar Automotive Holding and Aston Martin Lagonda, you can compare the effects of market volatilities on Polestar Automotive and Aston Martin 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 Polestar Automotive with a short position of Aston Martin. Check out your portfolio center. Please also check ongoing floating volatility patterns of Polestar Automotive and Aston Martin.
Diversification Opportunities for Polestar Automotive and Aston Martin
0.57 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Polestar and Aston is 0.57. Overlapping area represents the amount of risk that can be diversified away by holding Polestar Automotive Holding and Aston Martin Lagonda in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Aston Martin Lagonda and Polestar 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 Polestar Automotive Holding are associated (or correlated) with Aston Martin. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Aston Martin Lagonda has no effect on the direction of Polestar Automotive i.e., Polestar Automotive and Aston Martin go up and down completely randomly.
Pair Corralation between Polestar Automotive and Aston Martin
Assuming the 90 days horizon Polestar Automotive Holding is expected to under-perform the Aston Martin. In addition to that, Polestar Automotive is 2.02 times more volatile than Aston Martin Lagonda. It trades about -0.08 of its total potential returns per unit of risk. Aston Martin Lagonda is currently generating about -0.11 per unit of volatility. If you would invest 187.00 in Aston Martin Lagonda on September 2, 2024 and sell it today you would lose (56.00) from holding Aston Martin Lagonda or give up 29.95% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Polestar Automotive Holding vs. Aston Martin Lagonda
Performance |
Timeline |
Polestar Automotive |
Aston Martin Lagonda |
Polestar Automotive and Aston Martin Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Polestar Automotive and Aston Martin
The main advantage of trading using opposite Polestar Automotive and Aston Martin positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Polestar Automotive position performs unexpectedly, Aston Martin 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 Aston Martin will offset losses from the drop in Aston Martin's long position.Polestar Automotive vs. Lucid Group | Polestar Automotive vs. Canoo Inc | Polestar Automotive vs. Rivian Automotive | Polestar Automotive vs. Aston Martin Lagonda |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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