Correlation Between Mitsubishi Electric and Hon Hai
Can any of the company-specific risk be diversified away by investing in both Mitsubishi Electric and Hon Hai 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 Electric and Hon Hai into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mitsubishi Electric and Hon Hai Precision, you can compare the effects of market volatilities on Mitsubishi Electric and Hon Hai 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 Electric with a short position of Hon Hai. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mitsubishi Electric and Hon Hai.
Diversification Opportunities for Mitsubishi Electric and Hon Hai
0.46 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Mitsubishi and Hon is 0.46. Overlapping area represents the amount of risk that can be diversified away by holding Mitsubishi Electric and Hon Hai Precision in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hon Hai Precision and Mitsubishi Electric 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 Electric are associated (or correlated) with Hon Hai. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hon Hai Precision has no effect on the direction of Mitsubishi Electric i.e., Mitsubishi Electric and Hon Hai go up and down completely randomly.
Pair Corralation between Mitsubishi Electric and Hon Hai
Assuming the 90 days trading horizon Mitsubishi Electric is expected to generate 1.89 times less return on investment than Hon Hai. But when comparing it to its historical volatility, Mitsubishi Electric is 1.28 times less risky than Hon Hai. It trades about 0.03 of its potential returns per unit of risk. Hon Hai Precision is currently generating about 0.04 of returns per unit of risk over similar time horizon. If you would invest 1,030 in Hon Hai Precision on September 3, 2024 and sell it today you would earn a total of 60.00 from holding Hon Hai Precision or generate 5.83% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Mitsubishi Electric vs. Hon Hai Precision
Performance |
Timeline |
Mitsubishi Electric |
Hon Hai Precision |
Mitsubishi Electric and Hon Hai Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mitsubishi Electric and Hon Hai
The main advantage of trading using opposite Mitsubishi Electric and Hon Hai positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mitsubishi Electric position performs unexpectedly, Hon Hai 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 Hon Hai will offset losses from the drop in Hon Hai's long position.Mitsubishi Electric vs. Bausch Health Companies | Mitsubishi Electric vs. Geely Automobile Holdings | Mitsubishi Electric vs. Grupo Carso SAB | Mitsubishi Electric vs. Diamondrock Hospitality Co |
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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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