Correlation Between Matthews Asia and Vanguard Pacific
Can any of the company-specific risk be diversified away by investing in both Matthews Asia and Vanguard Pacific 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 Asia and Vanguard Pacific into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Matthews Asia Dividend and Vanguard Pacific Stock, you can compare the effects of market volatilities on Matthews Asia and Vanguard Pacific 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 Asia with a short position of Vanguard Pacific. Check out your portfolio center. Please also check ongoing floating volatility patterns of Matthews Asia and Vanguard Pacific.
Diversification Opportunities for Matthews Asia and Vanguard Pacific
0.79 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Matthews and Vanguard is 0.79. Overlapping area represents the amount of risk that can be diversified away by holding Matthews Asia Dividend and Vanguard Pacific Stock in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Vanguard Pacific Stock and Matthews Asia 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 Asia Dividend are associated (or correlated) with Vanguard Pacific. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Vanguard Pacific Stock has no effect on the direction of Matthews Asia i.e., Matthews Asia and Vanguard Pacific go up and down completely randomly.
Pair Corralation between Matthews Asia and Vanguard Pacific
Assuming the 90 days horizon Matthews Asia Dividend is expected to generate 0.84 times more return on investment than Vanguard Pacific. However, Matthews Asia Dividend is 1.19 times less risky than Vanguard Pacific. It trades about 0.05 of its potential returns per unit of risk. Vanguard Pacific Stock is currently generating about 0.02 per unit of risk. If you would invest 1,391 in Matthews Asia Dividend on September 1, 2024 and sell it today you would earn a total of 72.00 from holding Matthews Asia Dividend or generate 5.18% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Matthews Asia Dividend vs. Vanguard Pacific Stock
Performance |
Timeline |
Matthews Asia Dividend |
Vanguard Pacific Stock |
Matthews Asia and Vanguard Pacific Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Matthews Asia and Vanguard Pacific
The main advantage of trading using opposite Matthews Asia and Vanguard Pacific positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Matthews Asia position performs unexpectedly, Vanguard Pacific 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 Vanguard Pacific will offset losses from the drop in Vanguard Pacific's long position.Matthews Asia vs. Matthews Asian Growth | Matthews Asia vs. Matthews Pacific Tiger | Matthews Asia vs. Matthews Asia Growth | Matthews Asia vs. Matthews India Fund |
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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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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