Correlation Between Franklin High and Jpmorgan High
Can any of the company-specific risk be diversified away by investing in both Franklin High and Jpmorgan 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 Franklin High and Jpmorgan High into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Franklin High Yield and Jpmorgan High Yield, you can compare the effects of market volatilities on Franklin High and Jpmorgan 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 Franklin High with a short position of Jpmorgan High. Check out your portfolio center. Please also check ongoing floating volatility patterns of Franklin High and Jpmorgan High.
Diversification Opportunities for Franklin High and Jpmorgan High
0.57 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Franklin and Jpmorgan is 0.57. Overlapping area represents the amount of risk that can be diversified away by holding Franklin High Yield and Jpmorgan High Yield in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Jpmorgan High Yield and Franklin 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 Franklin High Yield are associated (or correlated) with Jpmorgan High. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Jpmorgan High Yield has no effect on the direction of Franklin High i.e., Franklin High and Jpmorgan High go up and down completely randomly.
Pair Corralation between Franklin High and Jpmorgan High
Assuming the 90 days horizon Franklin High Yield is expected to under-perform the Jpmorgan High. But the mutual fund apears to be less risky and, when comparing its historical volatility, Franklin High Yield is 1.08 times less risky than Jpmorgan High. The mutual fund trades about -0.43 of its potential returns per unit of risk. The Jpmorgan High Yield is currently generating about -0.29 of returns per unit of risk over similar time horizon. If you would invest 662.00 in Jpmorgan High Yield on September 30, 2024 and sell it today you would lose (11.00) from holding Jpmorgan High Yield or give up 1.66% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Franklin High Yield vs. Jpmorgan High Yield
Performance |
Timeline |
Franklin High Yield |
Jpmorgan High Yield |
Franklin High and Jpmorgan High Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Franklin High and Jpmorgan High
The main advantage of trading using opposite Franklin High and Jpmorgan High positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Franklin High position performs unexpectedly, Jpmorgan 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 Jpmorgan High will offset losses from the drop in Jpmorgan High's long position.Franklin High vs. Franklin Mutual Beacon | Franklin High vs. Templeton Developing Markets | Franklin High vs. Franklin Mutual Global | Franklin High vs. Franklin Mutual Global |
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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 Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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