Correlation Between Dow Jones and Arrow DWA

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Can any of the company-specific risk be diversified away by investing in both Dow Jones and Arrow DWA 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 Arrow DWA 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 Arrow DWA Tactical, you can compare the effects of market volatilities on Dow Jones and Arrow DWA 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 Arrow DWA. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dow Jones and Arrow DWA.

Diversification Opportunities for Dow Jones and Arrow DWA

-0.59
  Correlation Coefficient

Excellent diversification

The 3 months correlation between Dow and Arrow is -0.59. Overlapping area represents the amount of risk that can be diversified away by holding Dow Jones Industrial and Arrow DWA Tactical in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Arrow DWA Tactical 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 Arrow DWA. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Arrow DWA Tactical has no effect on the direction of Dow Jones i.e., Dow Jones and Arrow DWA go up and down completely randomly.
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Pair Corralation between Dow Jones and Arrow DWA

Assuming the 90 days trading horizon Dow Jones Industrial is expected to generate 1.02 times more return on investment than Arrow DWA. However, Dow Jones is 1.02 times more volatile than Arrow DWA Tactical. It trades about 0.21 of its potential returns per unit of risk. Arrow DWA Tactical is currently generating about -0.24 per unit of risk. If you would invest  4,237,436  in Dow Jones Industrial on August 25, 2024 and sell it today you would earn a total of  192,215  from holding Dow Jones Industrial or generate 4.54% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Against 
StrengthVery Weak
Accuracy100.0%
ValuesDaily Returns

Dow Jones Industrial  vs.  Arrow DWA Tactical

 Performance 
       Timeline  

Dow Jones and Arrow DWA Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with Dow Jones and Arrow DWA

The main advantage of trading using opposite Dow Jones and Arrow DWA positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dow Jones position performs unexpectedly, Arrow DWA 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 Arrow DWA will offset losses from the drop in Arrow DWA's long position.
The idea behind Dow Jones Industrial and Arrow DWA Tactical 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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