Correlation Between Cref Money and Ashmore Emerging
Can any of the company-specific risk be diversified away by investing in both Cref Money and Ashmore 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 Cref Money and Ashmore Emerging into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Cref Money Market and Ashmore Emerging Markets, you can compare the effects of market volatilities on Cref Money and Ashmore 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 Cref Money with a short position of Ashmore Emerging. Check out your portfolio center. Please also check ongoing floating volatility patterns of Cref Money and Ashmore Emerging.
Diversification Opportunities for Cref Money and Ashmore Emerging
0.9 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Cref and Ashmore is 0.9. Overlapping area represents the amount of risk that can be diversified away by holding Cref Money Market and Ashmore Emerging Markets in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ashmore Emerging Markets and Cref Money 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 Cref Money Market are associated (or correlated) with Ashmore Emerging. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ashmore Emerging Markets has no effect on the direction of Cref Money i.e., Cref Money and Ashmore Emerging go up and down completely randomly.
Pair Corralation between Cref Money and Ashmore Emerging
Assuming the 90 days trading horizon Cref Money is expected to generate 1.68 times less return on investment than Ashmore Emerging. But when comparing it to its historical volatility, Cref Money Market is 6.3 times less risky than Ashmore Emerging. It trades about 1.01 of its potential returns per unit of risk. Ashmore Emerging Markets is currently generating about 0.27 of returns per unit of risk over similar time horizon. If you would invest 875.00 in Ashmore Emerging Markets on December 29, 2024 and sell it today you would earn a total of 7.00 from holding Ashmore Emerging Markets or generate 0.8% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 45.9% |
Values | Daily Returns |
Cref Money Market vs. Ashmore Emerging Markets
Performance |
Timeline |
Cref Money Market |
Ashmore Emerging Markets |
Risk-Adjusted Performance
Solid
Weak | Strong |
Cref Money and Ashmore Emerging Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Cref Money and Ashmore Emerging
The main advantage of trading using opposite Cref Money and Ashmore Emerging positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Cref Money position performs unexpectedly, Ashmore 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 Ashmore Emerging will offset losses from the drop in Ashmore Emerging's long position.Cref Money vs. Nomura Real Estate | Cref Money vs. Cohen Steers Real | Cref Money vs. Nuveen Real Estate | Cref Money vs. Redwood Real Estate |
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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 Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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