Correlation Between Sri Trang and NYSE Composite

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

Diversification Opportunities for Sri Trang and NYSE Composite

0.77
  Correlation Coefficient

Poor diversification

The 3 months correlation between Sri and NYSE is 0.77. Overlapping area represents the amount of risk that can be diversified away by holding Sri Trang Agro Industry and NYSE Composite in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on NYSE Composite and Sri Trang 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 Sri Trang Agro Industry are associated (or correlated) with NYSE Composite. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of NYSE Composite has no effect on the direction of Sri Trang i.e., Sri Trang and NYSE Composite go up and down completely randomly.
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Pair Corralation between Sri Trang and NYSE Composite

Assuming the 90 days trading horizon Sri Trang Agro Industry is expected to under-perform the NYSE Composite. In addition to that, Sri Trang is 5.39 times more volatile than NYSE Composite. It trades about -0.12 of its total potential returns per unit of risk. NYSE Composite is currently generating about -0.07 per unit of volatility. If you would invest  1,815,437  in NYSE Composite on February 7, 2024 and sell it today you would lose (19,053) from holding NYSE Composite or give up 1.05% of portfolio value over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthSignificant
Accuracy76.19%
ValuesDaily Returns

Sri Trang Agro Industry  vs.  NYSE Composite

 Performance 
       Timeline  

Sri Trang and NYSE Composite Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with Sri Trang and NYSE Composite

The main advantage of trading using opposite Sri Trang and NYSE Composite positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sri Trang position performs unexpectedly, NYSE Composite 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 NYSE Composite will offset losses from the drop in NYSE Composite's long position.
The idea behind Sri Trang Agro Industry and NYSE Composite 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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