Correlation Between Amg Managers and Wstcm Credit
Can any of the company-specific risk be diversified away by investing in both Amg Managers and Wstcm Credit 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 Amg Managers and Wstcm Credit into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Amg Managers Centersquare and Wstcm Credit Select, you can compare the effects of market volatilities on Amg Managers and Wstcm Credit 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 Amg Managers with a short position of Wstcm Credit. Check out your portfolio center. Please also check ongoing floating volatility patterns of Amg Managers and Wstcm Credit.
Diversification Opportunities for Amg Managers and Wstcm Credit
-0.51 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Amg and Wstcm is -0.51. Overlapping area represents the amount of risk that can be diversified away by holding Amg Managers Centersquare and Wstcm Credit Select in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Wstcm Credit Select and Amg Managers 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 Amg Managers Centersquare are associated (or correlated) with Wstcm Credit. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Wstcm Credit Select has no effect on the direction of Amg Managers i.e., Amg Managers and Wstcm Credit go up and down completely randomly.
Pair Corralation between Amg Managers and Wstcm Credit
Assuming the 90 days horizon Amg Managers Centersquare is expected to generate 4.67 times more return on investment than Wstcm Credit. However, Amg Managers is 4.67 times more volatile than Wstcm Credit Select. It trades about 0.08 of its potential returns per unit of risk. Wstcm Credit Select is currently generating about 0.3 per unit of risk. If you would invest 1,041 in Amg Managers Centersquare on September 25, 2024 and sell it today you would earn a total of 96.00 from holding Amg Managers Centersquare or generate 9.22% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 52.8% |
Values | Daily Returns |
Amg Managers Centersquare vs. Wstcm Credit Select
Performance |
Timeline |
Amg Managers Centersquare |
Wstcm Credit Select |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Strong
Amg Managers and Wstcm Credit Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Amg Managers and Wstcm Credit
The main advantage of trading using opposite Amg Managers and Wstcm Credit positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Amg Managers position performs unexpectedly, Wstcm Credit 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 Wstcm Credit will offset losses from the drop in Wstcm Credit's long position.Amg Managers vs. Prudential Core Conservative | Amg Managers vs. Western Asset Diversified | Amg Managers vs. Wilmington Diversified Income | Amg Managers vs. Lord Abbett Diversified |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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