Correlation Between Gmo High and Power Dividend
Can any of the company-specific risk be diversified away by investing in both Gmo High and Power Dividend 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 Gmo High and Power Dividend into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Gmo High Yield and Power Dividend Index, you can compare the effects of market volatilities on Gmo High and Power Dividend 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 Gmo High with a short position of Power Dividend. Check out your portfolio center. Please also check ongoing floating volatility patterns of Gmo High and Power Dividend.
Diversification Opportunities for Gmo High and Power Dividend
0.78 | Correlation Coefficient |
Poor diversification
The 3 months correlation between GMO and Power is 0.78. Overlapping area represents the amount of risk that can be diversified away by holding Gmo High Yield and Power Dividend Index in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Power Dividend Index and Gmo High 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 Gmo High Yield are associated (or correlated) with Power Dividend. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Power Dividend Index has no effect on the direction of Gmo High i.e., Gmo High and Power Dividend go up and down completely randomly.
Pair Corralation between Gmo High and Power Dividend
Assuming the 90 days horizon Gmo High is expected to generate 2.48 times less return on investment than Power Dividend. But when comparing it to its historical volatility, Gmo High Yield is 4.32 times less risky than Power Dividend. It trades about 0.21 of its potential returns per unit of risk. Power Dividend Index is currently generating about 0.12 of returns per unit of risk over similar time horizon. If you would invest 931.00 in Power Dividend Index on September 3, 2024 and sell it today you would earn a total of 53.00 from holding Power Dividend Index or generate 5.69% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Gmo High Yield vs. Power Dividend Index
Performance |
Timeline |
Gmo High Yield |
Power Dividend Index |
Gmo High and Power Dividend Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Gmo High and Power Dividend
The main advantage of trading using opposite Gmo High and Power Dividend positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Gmo High position performs unexpectedly, Power Dividend 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 Dividend will offset losses from the drop in Power Dividend's long position.Gmo High vs. Vanguard High Yield Corporate | Gmo High vs. Vanguard High Yield Porate | Gmo High vs. Blackrock Hi Yld | Gmo High vs. Blackrock High Yield |
Power Dividend vs. T Rowe Price | Power Dividend vs. Lgm Risk Managed | Power Dividend vs. Gmo High Yield | Power Dividend vs. Guggenheim High Yield |
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 Sectors module to list of equity sectors categorizing publicly traded companies based on their primary business activities.
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