Correlation Between NYSE Composite and USCF ETF

Can any of the company-specific risk be diversified away by investing in both NYSE Composite and USCF ETF 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 USCF ETF into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between NYSE Composite and USCF ETF Trust, you can compare the effects of market volatilities on NYSE Composite and USCF ETF 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 USCF ETF. Check out your portfolio center. Please also check ongoing floating volatility patterns of NYSE Composite and USCF ETF.

Diversification Opportunities for NYSE Composite and USCF ETF

0.93

Correlation Coefficient

NYSE Composite  USCF ETF

Almost no diversification

The 3 months correlation between NYSE and USCF is 0.93. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and USCF ETF Trust in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on USCF ETF 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 USCF ETF. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of USCF ETF Trust has no effect on the direction of NYSE Composite i.e., NYSE Composite and USCF ETF go up and down completely randomly.

Pair Corralation between NYSE Composite and USCF ETF

Assuming the 90 days trading horizon NYSE Composite is expected to generate 1.14 times less return on investment than USCF ETF. But when comparing it to its historical volatility, NYSE Composite is 1.32 times less risky than USCF ETF. It trades about 0.17 of its potential returns per unit of risk. USCF ETF Trust is currently generating about 0.15 of returns per unit of risk over similar time horizon. If you would invest  2,920  in USCF ETF Trust on September 2, 2024 and sell it today you would earn a total of  218.00  from holding USCF ETF Trust or generate 7.47% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Very Strong
Accuracy	100.0%
Values	Daily Returns

NYSE Composite  vs.  USCF ETF Trust

Pair Trading with NYSE Composite and USCF ETF

The main advantage of trading using opposite NYSE Composite and USCF ETF positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NYSE Composite position performs unexpectedly, USCF ETF 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 USCF ETF will offset losses from the drop in USCF ETF's long position.

The idea behind NYSE Composite and USCF ETF Trust pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.

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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 Suggestion module to get suggestions outside of your existing asset allocation including your own model portfolios.