Correlation Between Mitsubishi Materials and Adidas AG
Can any of the company-specific risk be diversified away by investing in both Mitsubishi Materials and Adidas AG 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 Mitsubishi Materials and Adidas AG into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mitsubishi Materials and adidas AG, you can compare the effects of market volatilities on Mitsubishi Materials and Adidas AG 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 Mitsubishi Materials with a short position of Adidas AG. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mitsubishi Materials and Adidas AG.
Diversification Opportunities for Mitsubishi Materials and Adidas AG
-0.01 | Correlation Coefficient |
Good diversification
The 3 months correlation between Mitsubishi and Adidas is -0.01. Overlapping area represents the amount of risk that can be diversified away by holding Mitsubishi Materials and adidas AG in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on adidas AG and Mitsubishi Materials 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 Mitsubishi Materials are associated (or correlated) with Adidas AG. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of adidas AG has no effect on the direction of Mitsubishi Materials i.e., Mitsubishi Materials and Adidas AG go up and down completely randomly.
Pair Corralation between Mitsubishi Materials and Adidas AG
Assuming the 90 days trading horizon Mitsubishi Materials is expected to generate 11.14 times less return on investment than Adidas AG. But when comparing it to its historical volatility, Mitsubishi Materials is 1.02 times less risky than Adidas AG. It trades about 0.01 of its potential returns per unit of risk. adidas AG is currently generating about 0.16 of returns per unit of risk over similar time horizon. If you would invest 21,600 in adidas AG on October 25, 2024 and sell it today you would earn a total of 3,490 from holding adidas AG or generate 16.16% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Mitsubishi Materials vs. adidas AG
Performance |
Timeline |
Mitsubishi Materials |
adidas AG |
Mitsubishi Materials and Adidas AG Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mitsubishi Materials and Adidas AG
The main advantage of trading using opposite Mitsubishi Materials and Adidas AG positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mitsubishi Materials position performs unexpectedly, Adidas AG 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 Adidas AG will offset losses from the drop in Adidas AG's long position.Mitsubishi Materials vs. Apple Inc | Mitsubishi Materials vs. Apple Inc | Mitsubishi Materials vs. Apple Inc | Mitsubishi Materials vs. Apple Inc |
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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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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