Correlation Between NYSE Composite and BrainsWay

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

Diversification Opportunities for NYSE Composite and BrainsWay

-0.27
  Correlation Coefficient

Very good diversification

The 3 months correlation between NYSE and BrainsWay is -0.27. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and BrainsWay in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BrainsWay 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 BrainsWay. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BrainsWay has no effect on the direction of NYSE Composite i.e., NYSE Composite and BrainsWay go up and down completely randomly.
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Pair Corralation between NYSE Composite and BrainsWay

Assuming the 90 days trading horizon NYSE Composite is expected to generate 8.56 times less return on investment than BrainsWay. But when comparing it to its historical volatility, NYSE Composite is 15.69 times less risky than BrainsWay. It trades about 0.11 of its potential returns per unit of risk. BrainsWay is currently generating about 0.06 of returns per unit of risk over similar time horizon. If you would invest  297.00  in BrainsWay on September 26, 2024 and sell it today you would earn a total of  556.00  from holding BrainsWay or generate 187.21% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Against 
StrengthInsignificant
Accuracy100.0%
ValuesDaily Returns

NYSE Composite  vs.  BrainsWay

 Performance 
       Timeline  

NYSE Composite and BrainsWay Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with NYSE Composite and BrainsWay

The main advantage of trading using opposite NYSE Composite and BrainsWay positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NYSE Composite position performs unexpectedly, BrainsWay 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 BrainsWay will offset losses from the drop in BrainsWay's long position.
The idea behind NYSE Composite and BrainsWay 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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.

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