Correlation Between NYSE Composite and SUMITOMO

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

Diversification Opportunities for NYSE Composite and SUMITOMO

-0.6
  Correlation Coefficient

Excellent diversification

The 3 months correlation between NYSE and SUMITOMO is -0.6. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and SUMITOMO MITSUI FINL in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SUMITOMO MITSUI FINL 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 SUMITOMO. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SUMITOMO MITSUI FINL has no effect on the direction of NYSE Composite i.e., NYSE Composite and SUMITOMO go up and down completely randomly.
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Pair Corralation between NYSE Composite and SUMITOMO

Assuming the 90 days trading horizon NYSE Composite is expected to generate 2.48 times more return on investment than SUMITOMO. However, NYSE Composite is 2.48 times more volatile than SUMITOMO MITSUI FINL. It trades about 0.11 of its potential returns per unit of risk. SUMITOMO MITSUI FINL is currently generating about 0.01 per unit of risk. If you would invest  1,535,281  in NYSE Composite on August 31, 2024 and sell it today you would earn a total of  485,701  from holding NYSE Composite or generate 31.64% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Against 
StrengthWeak
Accuracy98.73%
ValuesDaily Returns

NYSE Composite  vs.  SUMITOMO MITSUI FINL

 Performance 
       Timeline  

NYSE Composite and SUMITOMO Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with NYSE Composite and SUMITOMO

The main advantage of trading using opposite NYSE Composite and SUMITOMO positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NYSE Composite position performs unexpectedly, SUMITOMO 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 SUMITOMO will offset losses from the drop in SUMITOMO's long position.
The idea behind NYSE Composite and SUMITOMO MITSUI FINL 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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.

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