Correlation Between Matthews China and Matthews China
Can any of the company-specific risk be diversified away by investing in both Matthews China and Matthews China 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 Matthews China and Matthews China into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Matthews China Dividend and Matthews China Fund, you can compare the effects of market volatilities on Matthews China and Matthews China 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 Matthews China with a short position of Matthews China. Check out your portfolio center. Please also check ongoing floating volatility patterns of Matthews China and Matthews China.
Diversification Opportunities for Matthews China and Matthews China
0.98 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Matthews and Matthews is 0.98. Overlapping area represents the amount of risk that can be diversified away by holding Matthews China Dividend and Matthews China Fund in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Matthews China and Matthews China 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 Matthews China Dividend are associated (or correlated) with Matthews China. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Matthews China has no effect on the direction of Matthews China i.e., Matthews China and Matthews China go up and down completely randomly.
Pair Corralation between Matthews China and Matthews China
Assuming the 90 days horizon Matthews China is expected to generate 6.3 times less return on investment than Matthews China. But when comparing it to its historical volatility, Matthews China Dividend is 1.34 times less risky than Matthews China. It trades about 0.0 of its potential returns per unit of risk. Matthews China Fund is currently generating about 0.02 of returns per unit of risk over similar time horizon. If you would invest 1,289 in Matthews China Fund on September 14, 2024 and sell it today you would earn a total of 137.00 from holding Matthews China Fund or generate 10.63% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Matthews China Dividend vs. Matthews China Fund
Performance |
Timeline |
Matthews China Dividend |
Matthews China |
Matthews China and Matthews China Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Matthews China and Matthews China
The main advantage of trading using opposite Matthews China and Matthews China positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Matthews China position performs unexpectedly, Matthews China 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 Matthews China will offset losses from the drop in Matthews China's long position.Matthews China vs. Matthews India Fund | Matthews China vs. Matthews China Dividend | Matthews China vs. Matthews Asia Growth |
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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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