Correlation Between Alliancebernstein and Legg Mason
Can any of the company-specific risk be diversified away by investing in both Alliancebernstein and Legg Mason 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 Alliancebernstein and Legg Mason into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Alliancebernstein Global Highome and Legg Mason Global, you can compare the effects of market volatilities on Alliancebernstein and Legg Mason 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 Alliancebernstein with a short position of Legg Mason. Check out your portfolio center. Please also check ongoing floating volatility patterns of Alliancebernstein and Legg Mason.
Diversification Opportunities for Alliancebernstein and Legg Mason
0.73 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Alliancebernstein and Legg is 0.73. Overlapping area represents the amount of risk that can be diversified away by holding Alliancebernstein Global Higho and Legg Mason Global in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Legg Mason Global and Alliancebernstein 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 Alliancebernstein Global Highome are associated (or correlated) with Legg Mason. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Legg Mason Global has no effect on the direction of Alliancebernstein i.e., Alliancebernstein and Legg Mason go up and down completely randomly.
Pair Corralation between Alliancebernstein and Legg Mason
Assuming the 90 days horizon Alliancebernstein Global Highome is expected to generate 0.28 times more return on investment than Legg Mason. However, Alliancebernstein Global Highome is 3.59 times less risky than Legg Mason. It trades about -0.31 of its potential returns per unit of risk. Legg Mason Global is currently generating about -0.35 per unit of risk. If you would invest 1,144 in Alliancebernstein Global Highome on October 9, 2024 and sell it today you would lose (13.00) from holding Alliancebernstein Global Highome or give up 1.14% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Alliancebernstein Global Higho vs. Legg Mason Global
Performance |
Timeline |
Alliancebernstein |
Legg Mason Global |
Alliancebernstein and Legg Mason Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Alliancebernstein and Legg Mason
The main advantage of trading using opposite Alliancebernstein and Legg Mason positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Alliancebernstein position performs unexpectedly, Legg Mason 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 Legg Mason will offset losses from the drop in Legg Mason's long position.Alliancebernstein vs. Alliancebernstein Bond | Alliancebernstein vs. Versatile Bond Portfolio | Alliancebernstein vs. Maryland Tax Free Bond | Alliancebernstein vs. Multisector Bond Sma |
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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 Valuation module to check real value of public entities based on technical and fundamental data.
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