Correlation Between Jpmorgan High and Federated Prudent
Can any of the company-specific risk be diversified away by investing in both Jpmorgan High and Federated Prudent 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 Jpmorgan High and Federated Prudent into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Jpmorgan High Yield and Federated Prudent Bear, you can compare the effects of market volatilities on Jpmorgan High and Federated Prudent 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 Jpmorgan High with a short position of Federated Prudent. Check out your portfolio center. Please also check ongoing floating volatility patterns of Jpmorgan High and Federated Prudent.
Diversification Opportunities for Jpmorgan High and Federated Prudent
-0.41 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Jpmorgan and Federated is -0.41. Overlapping area represents the amount of risk that can be diversified away by holding Jpmorgan High Yield and Federated Prudent Bear in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Federated Prudent Bear and Jpmorgan 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 Jpmorgan High Yield are associated (or correlated) with Federated Prudent. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Federated Prudent Bear has no effect on the direction of Jpmorgan High i.e., Jpmorgan High and Federated Prudent go up and down completely randomly.
Pair Corralation between Jpmorgan High and Federated Prudent
Assuming the 90 days horizon Jpmorgan High Yield is expected to generate 0.25 times more return on investment than Federated Prudent. However, Jpmorgan High Yield is 4.06 times less risky than Federated Prudent. It trades about 0.28 of its potential returns per unit of risk. Federated Prudent Bear is currently generating about -0.13 per unit of risk. If you would invest 651.00 in Jpmorgan High Yield on November 8, 2024 and sell it today you would earn a total of 7.00 from holding Jpmorgan High Yield or generate 1.08% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Jpmorgan High Yield vs. Federated Prudent Bear
Performance |
| Timeline |
| Jpmorgan High Yield |
| Federated Prudent Bear |
Jpmorgan High and Federated Prudent Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Jpmorgan High and Federated Prudent
The main advantage of trading using opposite Jpmorgan High and Federated Prudent positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Jpmorgan High position performs unexpectedly, Federated Prudent 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 Prudent will offset losses from the drop in Federated Prudent's long position.| Jpmorgan High vs. Voya Solution Conservative | Jpmorgan High vs. Jhancock Diversified Macro | Jpmorgan High vs. Global Diversified Income | Jpmorgan High vs. Diversified Income Fund |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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