Correlation Between Dow Jones and Beach Energy

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

Diversification Opportunities for Dow Jones and Beach Energy

0.22
  Correlation Coefficient

Modest diversification

The 3 months correlation between Dow and Beach is 0.22. Overlapping area represents the amount of risk that can be diversified away by holding Dow Jones Industrial and Beach Energy in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Beach Energy and Dow Jones 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 Dow Jones Industrial are associated (or correlated) with Beach Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Beach Energy has no effect on the direction of Dow Jones i.e., Dow Jones and Beach Energy go up and down completely randomly.
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Pair Corralation between Dow Jones and Beach Energy

Assuming the 90 days trading horizon Dow Jones Industrial is expected to generate 0.16 times more return on investment than Beach Energy. However, Dow Jones Industrial is 6.4 times less risky than Beach Energy. It trades about 0.09 of its potential returns per unit of risk. Beach Energy is currently generating about -0.02 per unit of risk. If you would invest  3,933,185  in Dow Jones Industrial on September 30, 2024 and sell it today you would earn a total of  366,036  from holding Dow Jones Industrial or generate 9.31% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthVery Weak
Accuracy98.43%
ValuesDaily Returns

Dow Jones Industrial  vs.  Beach Energy

 Performance 
       Timeline  

Dow Jones and Beach Energy Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with Dow Jones and Beach Energy

The main advantage of trading using opposite Dow Jones and Beach Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dow Jones position performs unexpectedly, Beach Energy 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 Beach Energy will offset losses from the drop in Beach Energy's long position.
The idea behind Dow Jones Industrial and Beach Energy 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 Fundamental Analysis module to view fundamental data based on most recent published financial statements.

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