Correlation Between NYSE Composite and Graph

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Can any of the company-specific risk be diversified away by investing in both NYSE Composite and Graph 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 Graph into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NYSE Composite and The Graph, you can compare the effects of market volatilities on NYSE Composite and Graph 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 Graph. Check out your portfolio center. Please also check ongoing floating volatility patterns of NYSE Composite and Graph.

Diversification Opportunities for NYSE Composite and Graph

0.74
  Correlation Coefficient

Poor diversification

The 3 months correlation between NYSE and Graph is 0.74. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and The Graph in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Graph 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 Graph. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Graph has no effect on the direction of NYSE Composite i.e., NYSE Composite and Graph go up and down completely randomly.
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Pair Corralation between NYSE Composite and Graph

Assuming the 90 days trading horizon NYSE Composite is expected to generate 15.63 times less return on investment than Graph. But when comparing it to its historical volatility, NYSE Composite is 9.52 times less risky than Graph. It trades about 0.29 of its potential returns per unit of risk. The Graph is currently generating about 0.47 of returns per unit of risk over similar time horizon. If you would invest  15.00  in The Graph on August 31, 2024 and sell it today you would earn a total of  12.00  from holding The Graph or generate 80.0% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthSignificant
Accuracy100.0%
ValuesDaily Returns

NYSE Composite  vs.  The Graph

 Performance 
       Timeline  

NYSE Composite and Graph Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with NYSE Composite and Graph

The main advantage of trading using opposite NYSE Composite and Graph positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NYSE Composite position performs unexpectedly, Graph 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 Graph will offset losses from the drop in Graph's long position.
The idea behind NYSE Composite and The Graph 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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.

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