Correlation Between NYSE Composite and Listed Funds
Can any of the company-specific risk be diversified away by investing in both NYSE Composite and Listed Funds 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 NYSE Composite and Listed Funds into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NYSE Composite and Listed Funds Trust, you can compare the effects of market volatilities on NYSE Composite and Listed Funds 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 NYSE Composite with a short position of Listed Funds. Check out your portfolio center. Please also check ongoing floating volatility patterns of NYSE Composite and Listed Funds.
Diversification Opportunities for NYSE Composite and Listed Funds
0.51 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between NYSE and Listed is 0.51. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and Listed Funds Trust in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Listed Funds Trust and NYSE Composite 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 NYSE Composite are associated (or correlated) with Listed Funds. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Listed Funds Trust has no effect on the direction of NYSE Composite i.e., NYSE Composite and Listed Funds go up and down completely randomly.
Pair Corralation between NYSE Composite and Listed Funds
Assuming the 90 days trading horizon NYSE Composite is expected to generate 1.97 times more return on investment than Listed Funds. However, NYSE Composite is 1.97 times more volatile than Listed Funds Trust. It trades about 0.07 of its potential returns per unit of risk. Listed Funds Trust is currently generating about 0.06 per unit of risk. If you would invest 1,564,892 in NYSE Composite on December 11, 2024 and sell it today you would earn a total of 355,346 from holding NYSE Composite or generate 22.71% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
NYSE Composite vs. Listed Funds Trust
Performance |
Timeline |
NYSE Composite and Listed Funds Volatility Contrast
Predicted Return Density |
Returns |
NYSE Composite
Pair trading matchups for NYSE Composite
Listed Funds Trust
Pair trading matchups for Listed Funds
Pair Trading with NYSE Composite and Listed Funds
The main advantage of trading using opposite NYSE Composite and Listed Funds positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NYSE Composite position performs unexpectedly, Listed Funds 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 Listed Funds will offset losses from the drop in Listed Funds' long position.NYSE Composite vs. AG Mortgage Investment | NYSE Composite vs. Western Asset Investment | NYSE Composite vs. PennantPark Investment | NYSE Composite vs. AG Mortgage Investment |
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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 Options Analysis module to analyze and evaluate options and option chains as a potential hedge for your portfolios.
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