Correlation Between Suzuki and Mercedes-Benz Group
Can any of the company-specific risk be diversified away by investing in both Suzuki 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 Suzuki 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 Suzuki Motor Corp and Mercedes Benz Group AG, you can compare the effects of market volatilities on Suzuki 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 Suzuki with a short position of Mercedes-Benz Group. Check out your portfolio center. Please also check ongoing floating volatility patterns of Suzuki and Mercedes-Benz Group.
Diversification Opportunities for Suzuki and Mercedes-Benz Group
0.66 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Suzuki and Mercedes-Benz is 0.66. Overlapping area represents the amount of risk that can be diversified away by holding Suzuki Motor Corp 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 Suzuki 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 Suzuki Motor Corp 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 Suzuki i.e., Suzuki and Mercedes-Benz Group go up and down completely randomly.
Pair Corralation between Suzuki and Mercedes-Benz Group
Assuming the 90 days horizon Suzuki Motor Corp is expected to generate 1.09 times more return on investment than Mercedes-Benz Group. However, Suzuki is 1.09 times more volatile than Mercedes Benz Group AG. It trades about 0.1 of its potential returns per unit of risk. Mercedes Benz Group AG is currently generating about 0.11 per unit of risk. If you would invest 4,527 in Suzuki Motor Corp on December 27, 2024 and sell it today you would earn a total of 513.00 from holding Suzuki Motor Corp or generate 11.33% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Suzuki Motor Corp vs. Mercedes Benz Group AG
Performance |
Timeline |
Suzuki Motor Corp |
Mercedes Benz Group |
Suzuki and Mercedes-Benz Group Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Suzuki and Mercedes-Benz Group
The main advantage of trading using opposite Suzuki and Mercedes-Benz Group positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Suzuki 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.Suzuki vs. Isuzu Motors | Suzuki vs. Honda Motor Co | Suzuki vs. Porsche Automobil Holding | Suzuki vs. Mazda Motor Corp |
Mercedes-Benz Group vs. Porsche Automobile Holding | Mercedes-Benz Group vs. Volkswagen AG 110 | Mercedes-Benz Group vs. Mercedes Benz Group AG | Mercedes-Benz Group vs. Volkswagen AG Pref |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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