Correlation Between Columbia Amt-free and Legg Mason
Can any of the company-specific risk be diversified away by investing in both Columbia Amt-free 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 Columbia Amt-free and Legg Mason into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Columbia Amt Free Intermediate and Legg Mason Partners, you can compare the effects of market volatilities on Columbia Amt-free 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 Columbia Amt-free with a short position of Legg Mason. Check out your portfolio center. Please also check ongoing floating volatility patterns of Columbia Amt-free and Legg Mason.
Diversification Opportunities for Columbia Amt-free and Legg Mason
0.02 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Columbia and Legg is 0.02. Overlapping area represents the amount of risk that can be diversified away by holding Columbia Amt Free Intermediate and Legg Mason Partners in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Legg Mason Partners and Columbia Amt-free 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 Columbia Amt Free Intermediate 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 Partners has no effect on the direction of Columbia Amt-free i.e., Columbia Amt-free and Legg Mason go up and down completely randomly.
Pair Corralation between Columbia Amt-free and Legg Mason
Assuming the 90 days horizon Columbia Amt Free Intermediate is expected to generate 0.13 times more return on investment than Legg Mason. However, Columbia Amt Free Intermediate is 7.89 times less risky than Legg Mason. It trades about -0.02 of its potential returns per unit of risk. Legg Mason Partners is currently generating about -0.08 per unit of risk. If you would invest 941.00 in Columbia Amt Free Intermediate on December 29, 2024 and sell it today you would lose (2.00) from holding Columbia Amt Free Intermediate or give up 0.21% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 98.39% |
Values | Daily Returns |
Columbia Amt Free Intermediate vs. Legg Mason Partners
Performance |
Timeline |
Columbia Amt Free |
Legg Mason Partners |
Columbia Amt-free and Legg Mason Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Columbia Amt-free and Legg Mason
The main advantage of trading using opposite Columbia Amt-free and Legg Mason positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Columbia Amt-free 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.Columbia Amt-free vs. Ep Emerging Markets | Columbia Amt-free vs. Oklahoma College Savings | Columbia Amt-free vs. Ab All Market | Columbia Amt-free vs. Doubleline Emerging Markets |
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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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