Correlation Between NYSE Composite and Aquila Tax-free
Can any of the company-specific risk be diversified away by investing in both NYSE Composite and Aquila Tax-free 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 Aquila Tax-free into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NYSE Composite and Aquila Tax Free Fund, you can compare the effects of market volatilities on NYSE Composite and Aquila Tax-free 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 Aquila Tax-free. Check out your portfolio center. Please also check ongoing floating volatility patterns of NYSE Composite and Aquila Tax-free.
Diversification Opportunities for NYSE Composite and Aquila Tax-free
0.68 | Correlation Coefficient |
Poor diversification
The 3 months correlation between NYSE and Aquila is 0.68. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and Aquila Tax Free Fund in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Aquila Tax Free 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 Aquila Tax-free. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Aquila Tax Free has no effect on the direction of NYSE Composite i.e., NYSE Composite and Aquila Tax-free go up and down completely randomly.
Pair Corralation between NYSE Composite and Aquila Tax-free
Assuming the 90 days trading horizon NYSE Composite is expected to under-perform the Aquila Tax-free. In addition to that, NYSE Composite is 3.63 times more volatile than Aquila Tax Free Fund. It trades about -0.04 of its total potential returns per unit of risk. Aquila Tax Free Fund is currently generating about -0.03 per unit of volatility. If you would invest 968.00 in Aquila Tax Free Fund on December 3, 2024 and sell it today you would lose (3.00) from holding Aquila Tax Free Fund or give up 0.31% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 98.36% |
Values | Daily Returns |
NYSE Composite vs. Aquila Tax Free Fund
Performance |
Timeline |
NYSE Composite and Aquila Tax-free Volatility Contrast
Predicted Return Density |
Returns |
NYSE Composite
Pair trading matchups for NYSE Composite
Aquila Tax Free Fund
Pair trading matchups for Aquila Tax-free
Pair Trading with NYSE Composite and Aquila Tax-free
The main advantage of trading using opposite NYSE Composite and Aquila Tax-free positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NYSE Composite position performs unexpectedly, Aquila Tax-free 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 Aquila Tax-free will offset losses from the drop in Aquila Tax-free's long position.NYSE Composite vs. Inflection Point Acquisition | NYSE Composite vs. Cardinal Health | NYSE Composite vs. Futuretech II Acquisition | NYSE Composite vs. Black Spade Acquisition |
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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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