Correlation Between Mitsubishi UFJ and UBS Group
Can any of the company-specific risk be diversified away by investing in both Mitsubishi UFJ and UBS 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 Mitsubishi UFJ and UBS Group into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mitsubishi UFJ Financial and UBS Group AG, you can compare the effects of market volatilities on Mitsubishi UFJ and UBS 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 Mitsubishi UFJ with a short position of UBS Group. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mitsubishi UFJ and UBS Group.
Diversification Opportunities for Mitsubishi UFJ and UBS Group
0.41 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Mitsubishi and UBS is 0.41. Overlapping area represents the amount of risk that can be diversified away by holding Mitsubishi UFJ Financial and UBS Group AG in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on UBS Group AG and Mitsubishi UFJ 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 UFJ Financial are associated (or correlated) with UBS Group. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of UBS Group AG has no effect on the direction of Mitsubishi UFJ i.e., Mitsubishi UFJ and UBS Group go up and down completely randomly.
Pair Corralation between Mitsubishi UFJ and UBS Group
Given the investment horizon of 90 days Mitsubishi UFJ Financial is expected to generate 0.85 times more return on investment than UBS Group. However, Mitsubishi UFJ Financial is 1.17 times less risky than UBS Group. It trades about 0.17 of its potential returns per unit of risk. UBS Group AG is currently generating about 0.03 per unit of risk. If you would invest 1,174 in Mitsubishi UFJ Financial on December 28, 2024 and sell it today you would earn a total of 224.00 from holding Mitsubishi UFJ Financial or generate 19.08% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Mitsubishi UFJ Financial vs. UBS Group AG
Performance |
Timeline |
Mitsubishi UFJ Financial |
UBS Group AG |
Mitsubishi UFJ and UBS Group Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mitsubishi UFJ and UBS Group
The main advantage of trading using opposite Mitsubishi UFJ and UBS Group positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mitsubishi UFJ position performs unexpectedly, UBS 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 UBS Group will offset losses from the drop in UBS Group's long position.Mitsubishi UFJ vs. Sumitomo Mitsui Financial | Mitsubishi UFJ vs. Mizuho Financial Group | Mitsubishi UFJ vs. Nomura Holdings ADR | Mitsubishi UFJ vs. Natwest Group PLC |
UBS Group vs. Citigroup | UBS Group vs. Barclays PLC ADR | UBS Group vs. HSBC Holdings PLC | UBS Group vs. Nu Holdings |
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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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