Correlation Between Pax High and Federated High
Can any of the company-specific risk be diversified away by investing in both Pax High and Federated High 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 Pax High and Federated High into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Pax High Yield and Federated High Income, you can compare the effects of market volatilities on Pax High and Federated High 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 Pax High with a short position of Federated High. Check out your portfolio center. Please also check ongoing floating volatility patterns of Pax High and Federated High.
Diversification Opportunities for Pax High and Federated High
0.79 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Pax and Federated is 0.79. Overlapping area represents the amount of risk that can be diversified away by holding Pax High Yield and Federated High Income in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Federated High Me and Pax 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 Pax High Yield are associated (or correlated) with Federated High. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Federated High Me has no effect on the direction of Pax High i.e., Pax High and Federated High go up and down completely randomly.
Pair Corralation between Pax High and Federated High
Assuming the 90 days horizon Pax High Yield is expected to under-perform the Federated High. In addition to that, Pax High is 1.21 times more volatile than Federated High Income. It trades about -0.32 of its total potential returns per unit of risk. Federated High Income is currently generating about -0.35 per unit of volatility. If you would invest 665.00 in Federated High Income on January 20, 2024 and sell it today you would lose (10.00) from holding Federated High Income or give up 1.5% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Pax High Yield vs. Federated High Income
Performance |
| Timeline |
| Pax High Yield |
| Federated High Me |
Pax High and Federated High Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Pax High and Federated High
The main advantage of trading using opposite Pax High and Federated High positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Pax High position performs unexpectedly, Federated High 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 Federated High will offset losses from the drop in Federated High's long position.| Pax High vs. Vanguard High Yield Porate | Pax High vs. Blackrock Hi Yld | Pax High vs. American Funds American | Pax High vs. American Funds American |
| Federated High vs. California High Yield Municipal | Federated High vs. Western Asset High | Federated High vs. T Rowe Price | Federated High vs. Fa 529 Aggressive |
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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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