Correlation Between Bayerische Motoren and Toyota
Can any of the company-specific risk be diversified away by investing in both Bayerische Motoren and Toyota 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 Bayerische Motoren and Toyota into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bayerische Motoren Werke and Toyota Motor, you can compare the effects of market volatilities on Bayerische Motoren and Toyota 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 Bayerische Motoren with a short position of Toyota. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bayerische Motoren and Toyota.
Diversification Opportunities for Bayerische Motoren and Toyota
0.25 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Bayerische and Toyota is 0.25. Overlapping area represents the amount of risk that can be diversified away by holding Bayerische Motoren Werke and Toyota Motor in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Toyota Motor and Bayerische Motoren 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 Bayerische Motoren Werke are associated (or correlated) with Toyota. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Toyota Motor has no effect on the direction of Bayerische Motoren i.e., Bayerische Motoren and Toyota go up and down completely randomly.
Pair Corralation between Bayerische Motoren and Toyota
Assuming the 90 days trading horizon Bayerische Motoren Werke is expected to generate 0.81 times more return on investment than Toyota. However, Bayerische Motoren Werke is 1.24 times less risky than Toyota. It trades about 0.08 of its potential returns per unit of risk. Toyota Motor is currently generating about -0.05 per unit of risk. If you would invest 149,698 in Bayerische Motoren Werke on September 17, 2024 and sell it today you would earn a total of 11,724 from holding Bayerische Motoren Werke or generate 7.83% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 48.39% |
Values | Daily Returns |
Bayerische Motoren Werke vs. Toyota Motor
Performance |
Timeline |
Bayerische Motoren Werke |
Toyota Motor |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
Bayerische Motoren and Toyota Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bayerische Motoren and Toyota
The main advantage of trading using opposite Bayerische Motoren and Toyota positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bayerische Motoren position performs unexpectedly, Toyota 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 Toyota will offset losses from the drop in Toyota's long position.Bayerische Motoren vs. Tesla Inc | Bayerische Motoren vs. iShares Global Timber | Bayerische Motoren vs. Vanguard World | Bayerische Motoren vs. iShares Trust |
Toyota vs. Tesla Inc | Toyota vs. Bayerische Motoren Werke | Toyota vs. iShares Global Timber | Toyota vs. Vanguard World |
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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