Correlation Between Mitsubishi UFJ and SSC Technologies
Can any of the company-specific risk be diversified away by investing in both Mitsubishi UFJ and SSC Technologies 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 SSC Technologies 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 SSC Technologies Holdings, you can compare the effects of market volatilities on Mitsubishi UFJ and SSC Technologies 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 SSC Technologies. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mitsubishi UFJ and SSC Technologies.
Diversification Opportunities for Mitsubishi UFJ and SSC Technologies
0.8 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Mitsubishi and SSC is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding Mitsubishi UFJ Financial and SSC Technologies Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SSC Technologies 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 SSC Technologies. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SSC Technologies Holdings has no effect on the direction of Mitsubishi UFJ i.e., Mitsubishi UFJ and SSC Technologies go up and down completely randomly.
Pair Corralation between Mitsubishi UFJ and SSC Technologies
Assuming the 90 days trading horizon Mitsubishi UFJ Financial is expected to under-perform the SSC Technologies. In addition to that, Mitsubishi UFJ is 1.36 times more volatile than SSC Technologies Holdings. It trades about -0.02 of its total potential returns per unit of risk. SSC Technologies Holdings is currently generating about -0.01 per unit of volatility. If you would invest 7,275 in SSC Technologies Holdings on September 27, 2024 and sell it today you would lose (25.00) from holding SSC Technologies Holdings or give up 0.34% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Mitsubishi UFJ Financial vs. SSC Technologies Holdings
Performance |
Timeline |
Mitsubishi UFJ Financial |
SSC Technologies Holdings |
Mitsubishi UFJ and SSC Technologies Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mitsubishi UFJ and SSC Technologies
The main advantage of trading using opposite Mitsubishi UFJ and SSC Technologies positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mitsubishi UFJ position performs unexpectedly, SSC Technologies 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 SSC Technologies will offset losses from the drop in SSC Technologies' long position.Mitsubishi UFJ vs. JPMorgan Chase Co | Mitsubishi UFJ vs. Wells Fargo | Mitsubishi UFJ vs. HSBC Holdings plc | Mitsubishi UFJ vs. Citigroup |
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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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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