Correlation Between NYSE Composite and Bellicum Pharmaceuticals

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

Diversification Opportunities for NYSE Composite and Bellicum Pharmaceuticals

0.07
  Correlation Coefficient

Significant diversification

The 3 months correlation between NYSE and Bellicum is 0.07. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and Bellicum Pharmaceuticals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bellicum Pharmaceuticals 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 Bellicum Pharmaceuticals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bellicum Pharmaceuticals has no effect on the direction of NYSE Composite i.e., NYSE Composite and Bellicum Pharmaceuticals go up and down completely randomly.
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Pair Corralation between NYSE Composite and Bellicum Pharmaceuticals

If you would invest  1,954,967  in NYSE Composite on August 27, 2024 and sell it today you would earn a total of  57,378  from holding NYSE Composite or generate 2.93% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthInsignificant
Accuracy4.76%
ValuesDaily Returns

NYSE Composite  vs.  Bellicum Pharmaceuticals

 Performance 
       Timeline  

NYSE Composite and Bellicum Pharmaceuticals Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with NYSE Composite and Bellicum Pharmaceuticals

The main advantage of trading using opposite NYSE Composite and Bellicum Pharmaceuticals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NYSE Composite position performs unexpectedly, Bellicum Pharmaceuticals 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 Bellicum Pharmaceuticals will offset losses from the drop in Bellicum Pharmaceuticals' long position.
The idea behind NYSE Composite and Bellicum Pharmaceuticals 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 Correlation Analysis module to reduce portfolio risk simply by holding instruments which are not perfectly correlated.

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