Correlation Between Advent Claymore and Multisector Bond
Can any of the company-specific risk be diversified away by investing in both Advent Claymore and Multisector Bond 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 Advent Claymore and Multisector Bond into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Advent Claymore Convertible and Multisector Bond Sma, you can compare the effects of market volatilities on Advent Claymore and Multisector Bond 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 Advent Claymore with a short position of Multisector Bond. Check out your portfolio center. Please also check ongoing floating volatility patterns of Advent Claymore and Multisector Bond.
Diversification Opportunities for Advent Claymore and Multisector Bond
0.9 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Advent and Multisector is 0.9. Overlapping area represents the amount of risk that can be diversified away by holding Advent Claymore Convertible and Multisector Bond Sma in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Multisector Bond Sma and Advent Claymore 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 Advent Claymore Convertible are associated (or correlated) with Multisector Bond. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Multisector Bond Sma has no effect on the direction of Advent Claymore i.e., Advent Claymore and Multisector Bond go up and down completely randomly.
Pair Corralation between Advent Claymore and Multisector Bond
Assuming the 90 days horizon Advent Claymore Convertible is expected to generate 2.16 times more return on investment than Multisector Bond. However, Advent Claymore is 2.16 times more volatile than Multisector Bond Sma. It trades about 0.15 of its potential returns per unit of risk. Multisector Bond Sma is currently generating about 0.24 per unit of risk. If you would invest 1,217 in Advent Claymore Convertible on May 17, 2025 and sell it today you would earn a total of 67.00 from holding Advent Claymore Convertible or generate 5.51% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Advent Claymore Convertible vs. Multisector Bond Sma
Performance |
Timeline |
Advent Claymore Conv |
Multisector Bond Sma |
Advent Claymore and Multisector Bond Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Advent Claymore and Multisector Bond
The main advantage of trading using opposite Advent Claymore and Multisector Bond positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Advent Claymore position performs unexpectedly, Multisector Bond 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 Multisector Bond will offset losses from the drop in Multisector Bond's long position.Advent Claymore vs. Siit Large Cap | Advent Claymore vs. M Large Cap | Advent Claymore vs. Vest Large Cap | Advent Claymore vs. Guidemark Large Cap |
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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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