Correlation Between High Yield and High Yield
Can any of the company-specific risk be diversified away by investing in both High Yield and High Yield 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 High Yield into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between High Yield Fund Investor and High Yield Municipal Fund, you can compare the effects of market volatilities on High Yield and High Yield 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 High Yield. Check out your portfolio center. Please also check ongoing floating volatility patterns of High Yield and High Yield.
Diversification Opportunities for High Yield and High Yield
0.68 | Correlation Coefficient |
Poor diversification
The 3 months correlation between High and High is 0.68. Overlapping area represents the amount of risk that can be diversified away by holding High Yield Fund Investor and High Yield Municipal Fund in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on High Yield Municipal 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 Fund Investor are associated (or correlated) with High Yield. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of High Yield Municipal has no effect on the direction of High Yield i.e., High Yield and High Yield go up and down completely randomly.
Pair Corralation between High Yield and High Yield
Assuming the 90 days horizon High Yield is expected to generate 3.12 times less return on investment than High Yield. In addition to that, High Yield is 1.16 times more volatile than High Yield Municipal Fund. It trades about 0.12 of its total potential returns per unit of risk. High Yield Municipal Fund is currently generating about 0.45 per unit of volatility. If you would invest 893.00 in High Yield Municipal Fund on September 13, 2024 and sell it today you would earn a total of 11.00 from holding High Yield Municipal Fund or generate 1.23% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
High Yield Fund Investor vs. High Yield Municipal Fund
Performance |
Timeline |
High Yield Fund |
High Yield Municipal |
High Yield and High Yield Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with High Yield and High Yield
The main advantage of trading using opposite High Yield and High Yield positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if High Yield position performs unexpectedly, High Yield 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 High Yield will offset losses from the drop in High Yield's long position.High Yield vs. High Yield Municipal Fund | High Yield vs. Diversified Bond Fund | High Yield vs. Ginnie Mae Fund | High Yield vs. Utilities Fund Investor |
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 |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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