Correlation Between Mainstay Convertible and Power Income
Can any of the company-specific risk be diversified away by investing in both Mainstay Convertible and Power Income 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 Mainstay Convertible and Power Income into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mainstay Vertible Fund and Power Income Fund, you can compare the effects of market volatilities on Mainstay Convertible and Power Income 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 Mainstay Convertible with a short position of Power Income. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mainstay Convertible and Power Income.
Diversification Opportunities for Mainstay Convertible and Power Income
-0.25 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Mainstay and Power is -0.25. Overlapping area represents the amount of risk that can be diversified away by holding Mainstay Vertible Fund and Power Income Fund in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Power Income and Mainstay Convertible 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 Mainstay Vertible Fund are associated (or correlated) with Power Income. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Power Income has no effect on the direction of Mainstay Convertible i.e., Mainstay Convertible and Power Income go up and down completely randomly.
Pair Corralation between Mainstay Convertible and Power Income
Assuming the 90 days horizon Mainstay Vertible Fund is expected to under-perform the Power Income. In addition to that, Mainstay Convertible is 2.15 times more volatile than Power Income Fund. It trades about -0.04 of its total potential returns per unit of risk. Power Income Fund is currently generating about 0.1 per unit of volatility. If you would invest 895.00 in Power Income Fund on December 20, 2024 and sell it today you would earn a total of 14.00 from holding Power Income Fund or generate 1.56% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Mainstay Vertible Fund vs. Power Income Fund
Performance |
Timeline |
Mainstay Convertible |
Power Income |
Mainstay Convertible and Power Income Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mainstay Convertible and Power Income
The main advantage of trading using opposite Mainstay Convertible and Power Income positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mainstay Convertible position performs unexpectedly, Power Income 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 Power Income will offset losses from the drop in Power Income's long position.Mainstay Convertible vs. Mainstay High Yield | Mainstay Convertible vs. Mainstay Income Builder | Mainstay Convertible vs. Mainstay Sp 500 | Mainstay Convertible vs. Mainstay 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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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