Correlation Between Payden Gnma and Payden Core
Can any of the company-specific risk be diversified away by investing in both Payden Gnma and Payden Core 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 Payden Gnma and Payden Core into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Payden Gnma Fund and Payden Core Bond, you can compare the effects of market volatilities on Payden Gnma and Payden Core 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 Payden Gnma with a short position of Payden Core. Check out your portfolio center. Please also check ongoing floating volatility patterns of Payden Gnma and Payden Core.
Diversification Opportunities for Payden Gnma and Payden Core
0.98 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Payden and Payden is 0.98. Overlapping area represents the amount of risk that can be diversified away by holding Payden Gnma Fund and Payden Core Bond in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Payden Core Bond and Payden Gnma 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 Payden Gnma Fund are associated (or correlated) with Payden Core. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Payden Core Bond has no effect on the direction of Payden Gnma i.e., Payden Gnma and Payden Core go up and down completely randomly.
Pair Corralation between Payden Gnma and Payden Core
Assuming the 90 days horizon Payden Gnma Fund is expected to generate 1.19 times more return on investment than Payden Core. However, Payden Gnma is 1.19 times more volatile than Payden Core Bond. It trades about 0.04 of its potential returns per unit of risk. Payden Core Bond is currently generating about 0.04 per unit of risk. If you would invest 761.00 in Payden Gnma Fund on December 2, 2024 and sell it today you would earn a total of 6.00 from holding Payden Gnma Fund or generate 0.79% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Payden Gnma Fund vs. Payden Core Bond
Performance |
Timeline |
Payden Gnma Fund |
Payden Core Bond |
Payden Gnma and Payden Core Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Payden Gnma and Payden Core
The main advantage of trading using opposite Payden Gnma and Payden Core positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Payden Gnma position performs unexpectedly, Payden Core 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 Payden Core will offset losses from the drop in Payden Core's long position.Payden Gnma vs. Fidelity Managed Retirement | Payden Gnma vs. Franklin Moderate Allocation | Payden Gnma vs. American Funds Retirement | Payden Gnma vs. Tiaa Cref Lifestyle Moderate |
Payden Core vs. Nuveen Small Cap | Payden Core vs. Franklin Small Cap | Payden Core vs. Old Westbury Small | Payden Core vs. Legg Mason Partners |
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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