Correlation Between American Funds and Dws Emerging
Can any of the company-specific risk be diversified away by investing in both American Funds and Dws Emerging 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 American Funds and Dws Emerging into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between American Funds New and Dws Emerging Markets, you can compare the effects of market volatilities on American Funds and Dws Emerging 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 American Funds with a short position of Dws Emerging. Check out your portfolio center. Please also check ongoing floating volatility patterns of American Funds and Dws Emerging.
Diversification Opportunities for American Funds and Dws Emerging
0.89 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between American and Dws is 0.89. Overlapping area represents the amount of risk that can be diversified away by holding American Funds New and Dws Emerging Markets in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dws Emerging Markets and American Funds 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 American Funds New are associated (or correlated) with Dws Emerging. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dws Emerging Markets has no effect on the direction of American Funds i.e., American Funds and Dws Emerging go up and down completely randomly.
Pair Corralation between American Funds and Dws Emerging
Assuming the 90 days horizon American Funds New is expected to under-perform the Dws Emerging. But the mutual fund apears to be less risky and, when comparing its historical volatility, American Funds New is 1.46 times less risky than Dws Emerging. The mutual fund trades about -0.03 of its potential returns per unit of risk. The Dws Emerging Markets is currently generating about 0.03 of returns per unit of risk over similar time horizon. If you would invest 1,915 in Dws Emerging Markets on September 12, 2024 and sell it today you would earn a total of 10.00 from holding Dws Emerging Markets or generate 0.52% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
American Funds New vs. Dws Emerging Markets
Performance |
Timeline |
American Funds New |
Dws Emerging Markets |
American Funds and Dws Emerging Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with American Funds and Dws Emerging
The main advantage of trading using opposite American Funds and Dws Emerging positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if American Funds position performs unexpectedly, Dws Emerging 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 Dws Emerging will offset losses from the drop in Dws Emerging's long position.American Funds vs. Elfun Government Money | American Funds vs. Edward Jones Money | American Funds vs. Aig Government Money | American Funds vs. Franklin Government Money |
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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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