Correlation Between Amg Managers and Morgan Stanley
Can any of the company-specific risk be diversified away by investing in both Amg Managers and Morgan Stanley 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 Morgan Stanley 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 Morgan Stanley European, you can compare the effects of market volatilities on Amg Managers and Morgan Stanley 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 Morgan Stanley. Check out your portfolio center. Please also check ongoing floating volatility patterns of Amg Managers and Morgan Stanley.
Diversification Opportunities for Amg Managers and Morgan Stanley
0.26 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Amg and Morgan is 0.26. Overlapping area represents the amount of risk that can be diversified away by holding Amg Managers Centersquare and Morgan Stanley European in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Morgan Stanley European 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 Morgan Stanley. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Morgan Stanley European has no effect on the direction of Amg Managers i.e., Amg Managers and Morgan Stanley go up and down completely randomly.
Pair Corralation between Amg Managers and Morgan Stanley
Assuming the 90 days horizon Amg Managers is expected to generate 14.36 times less return on investment than Morgan Stanley. But when comparing it to its historical volatility, Amg Managers Centersquare is 1.01 times less risky than Morgan Stanley. It trades about 0.04 of its potential returns per unit of risk. Morgan Stanley European is currently generating about 0.53 of returns per unit of risk over similar time horizon. If you would invest 2,322 in Morgan Stanley European on September 13, 2024 and sell it today you would earn a total of 190.00 from holding Morgan Stanley European or generate 8.18% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Amg Managers Centersquare vs. Morgan Stanley European
Performance |
Timeline |
Amg Managers Centersquare |
Morgan Stanley European |
Amg Managers and Morgan Stanley Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Amg Managers and Morgan Stanley
The main advantage of trading using opposite Amg Managers and Morgan Stanley positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Amg Managers position performs unexpectedly, Morgan Stanley 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 Morgan Stanley will offset losses from the drop in Morgan Stanley's long position.Amg Managers vs. Realty Income | Amg Managers vs. Dynex Capital | Amg Managers vs. First Industrial Realty | Amg Managers vs. Healthcare Realty Trust |
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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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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