Correlation Between NYSE Composite and 459200KX8

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Can any of the company-specific risk be diversified away by investing in both NYSE Composite and 459200KX8 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 459200KX8 into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NYSE Composite and IBM 45 06 FEB 28, you can compare the effects of market volatilities on NYSE Composite and 459200KX8 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 459200KX8. Check out your portfolio center. Please also check ongoing floating volatility patterns of NYSE Composite and 459200KX8.

Diversification Opportunities for NYSE Composite and 459200KX8

-0.69
  Correlation Coefficient

Excellent diversification

The 3 months correlation between NYSE and 459200KX8 is -0.69. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and IBM 45 06 FEB 28 in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on IBM 45 06 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 459200KX8. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of IBM 45 06 has no effect on the direction of NYSE Composite i.e., NYSE Composite and 459200KX8 go up and down completely randomly.
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Pair Corralation between NYSE Composite and 459200KX8

Assuming the 90 days trading horizon NYSE Composite is expected to generate 2.59 times more return on investment than 459200KX8. However, NYSE Composite is 2.59 times more volatile than IBM 45 06 FEB 28. It trades about 0.24 of its potential returns per unit of risk. IBM 45 06 FEB 28 is currently generating about 0.13 per unit of risk. If you would invest  1,954,967  in NYSE Composite on August 29, 2024 and sell it today you would earn a total of  66,978  from holding NYSE Composite or generate 3.43% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Against 
StrengthWeak
Accuracy100.0%
ValuesDaily Returns

NYSE Composite  vs.  IBM 45 06 FEB 28

 Performance 
       Timeline  

NYSE Composite and 459200KX8 Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with NYSE Composite and 459200KX8

The main advantage of trading using opposite NYSE Composite and 459200KX8 positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NYSE Composite position performs unexpectedly, 459200KX8 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 459200KX8 will offset losses from the drop in 459200KX8's long position.
The idea behind NYSE Composite and IBM 45 06 FEB 28 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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.

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