Correlation Between NYSE Composite and SEI Select

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

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

Diversification Opportunities for NYSE Composite and SEI Select

0.19

Correlation Coefficient

NYSE Composite  SEI Select

Average diversification

The 3 months correlation between NYSE and SEI is 0.19. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and SEI Select Emerging in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SEI Select Emerging 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 SEI Select. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SEI Select Emerging has no effect on the direction of NYSE Composite i.e., NYSE Composite and SEI Select go up and down completely randomly.

Pair Corralation between NYSE Composite and SEI Select

Assuming the 90 days trading horizon NYSE Composite is expected to under-perform the SEI Select. But the index apears to be less risky and, when comparing its historical volatility, NYSE Composite is 1.18 times less risky than SEI Select. The index trades about -0.13 of its potential returns per unit of risk. The SEI Select Emerging is currently generating about -0.09 of returns per unit of risk over similar time horizon. If you would invest  2,426  in SEI Select Emerging on October 9, 2024 and sell it today you would lose (69.00) from holding SEI Select Emerging or give up 2.84% of portfolio value over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Insignificant
Accuracy	97.5%
Values	Daily Returns

NYSE Composite  vs.  SEI Select Emerging

Pair Trading with NYSE Composite and SEI Select

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

The idea behind NYSE Composite and SEI Select Emerging 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 Competition Analyzer module to analyze and compare many basic indicators for a group of related or unrelated entities.