Correlation Between Global Real and Multisector Bond
Can any of the company-specific risk be diversified away by investing in both Global Real 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 Global Real and Multisector Bond into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Global Real Estate and Multisector Bond Sma, you can compare the effects of market volatilities on Global Real 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 Global Real with a short position of Multisector Bond. Check out your portfolio center. Please also check ongoing floating volatility patterns of Global Real and Multisector Bond.
Diversification Opportunities for Global Real and Multisector Bond
0.85 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Global and Multisector is 0.85. Overlapping area represents the amount of risk that can be diversified away by holding Global Real Estate 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 Global Real 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 Global Real Estate 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 Global Real i.e., Global Real and Multisector Bond go up and down completely randomly.
Pair Corralation between Global Real and Multisector Bond
Assuming the 90 days horizon Global Real Estate is expected to generate 2.06 times more return on investment than Multisector Bond. However, Global Real is 2.06 times more volatile than Multisector Bond Sma. It trades about 0.13 of its potential returns per unit of risk. Multisector Bond Sma is currently generating about -0.04 per unit of risk. If you would invest 690.00 in Global Real Estate on April 27, 2025 and sell it today you would earn a total of 10.00 from holding Global Real Estate or generate 1.45% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Global Real Estate vs. Multisector Bond Sma
Performance |
Timeline |
Global Real Estate |
Multisector Bond Sma |
Global Real and Multisector Bond Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Global Real and Multisector Bond
The main advantage of trading using opposite Global Real and Multisector Bond positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Global Real 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.Global Real vs. Virtus Convertible | Global Real vs. Rationalpier 88 Convertible | Global Real vs. Advent Claymore Convertible | Global Real vs. Absolute Convertible Arbitrage |
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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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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