Correlation Between High Yield and Global X
Can any of the company-specific risk be diversified away by investing in both High Yield and Global X 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 High Yield and Global X into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between High Yield Municipal Fund and Global X MSCI, you can compare the effects of market volatilities on High Yield and Global X 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 High Yield with a short position of Global X. Check out your portfolio center. Please also check ongoing floating volatility patterns of High Yield and Global X.
Diversification Opportunities for High Yield and Global X
0.33 | Correlation Coefficient |
Weak diversification
The 3 months correlation between High and Global is 0.33. Overlapping area represents the amount of risk that can be diversified away by holding High Yield Municipal Fund and Global X MSCI in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Global X MSCI and High Yield 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 High Yield Municipal Fund are associated (or correlated) with Global X. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Global X MSCI has no effect on the direction of High Yield i.e., High Yield and Global X go up and down completely randomly.
Pair Corralation between High Yield and Global X
Assuming the 90 days horizon High Yield is expected to generate 7.11 times less return on investment than Global X. But when comparing it to its historical volatility, High Yield Municipal Fund is 4.78 times less risky than Global X. It trades about 0.04 of its potential returns per unit of risk. Global X MSCI is currently generating about 0.06 of returns per unit of risk over similar time horizon. If you would invest 2,392 in Global X MSCI on September 13, 2024 and sell it today you would earn a total of 106.86 from holding Global X MSCI or generate 4.47% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 98.44% |
Values | Daily Returns |
High Yield Municipal Fund vs. Global X MSCI
Performance |
Timeline |
High Yield Municipal |
Global X MSCI |
High Yield and Global X Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with High Yield and Global X
The main advantage of trading using opposite High Yield and Global X positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if High Yield position performs unexpectedly, Global X 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 Global X will offset losses from the drop in Global X's long position.High Yield vs. High Yield Fund Investor | High Yield vs. Intermediate Term Tax Free Bond | High Yield vs. California High Yield Municipal | High Yield vs. T Rowe Price |
Global X vs. Global X MSCI | Global X vs. Global X Alternative | Global X vs. iShares Emerging Markets | Global X vs. Global X SuperDividend |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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