Correlation Between Mitsubishi UFJ and Tencent Holdings
Can any of the company-specific risk be diversified away by investing in both Mitsubishi UFJ and Tencent Holdings 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 Tencent Holdings 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 Tencent Holdings Ltd, you can compare the effects of market volatilities on Mitsubishi UFJ and Tencent Holdings 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 Tencent Holdings. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mitsubishi UFJ and Tencent Holdings.
Diversification Opportunities for Mitsubishi UFJ and Tencent Holdings
-0.4 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Mitsubishi and Tencent is -0.4. Overlapping area represents the amount of risk that can be diversified away by holding Mitsubishi UFJ Financial and Tencent Holdings Ltd in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Tencent Holdings 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 Tencent Holdings. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Tencent Holdings has no effect on the direction of Mitsubishi UFJ i.e., Mitsubishi UFJ and Tencent Holdings go up and down completely randomly.
Pair Corralation between Mitsubishi UFJ and Tencent Holdings
Assuming the 90 days horizon Mitsubishi UFJ Financial is expected to generate 1.92 times more return on investment than Tencent Holdings. However, Mitsubishi UFJ is 1.92 times more volatile than Tencent Holdings Ltd. It trades about 0.1 of its potential returns per unit of risk. Tencent Holdings Ltd is currently generating about 0.17 per unit of risk. If you would invest 1,082 in Mitsubishi UFJ Financial on September 23, 2024 and sell it today you would earn a total of 68.00 from holding Mitsubishi UFJ Financial or generate 6.28% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Mitsubishi UFJ Financial vs. Tencent Holdings Ltd
Performance |
Timeline |
Mitsubishi UFJ Financial |
Tencent Holdings |
Mitsubishi UFJ and Tencent Holdings Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mitsubishi UFJ and Tencent Holdings
The main advantage of trading using opposite Mitsubishi UFJ and Tencent Holdings positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mitsubishi UFJ position performs unexpectedly, Tencent Holdings 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 Tencent Holdings will offset losses from the drop in Tencent Holdings' long position.Mitsubishi UFJ vs. China Construction Bank | Mitsubishi UFJ vs. National Australia Bank | Mitsubishi UFJ vs. Svenska Handelsbanken AB | Mitsubishi UFJ vs. Bank of America |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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