Correlation Between Dow Jones and Bbh Income

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

Diversification Opportunities for Dow Jones and Bbh Income

0.06
  Correlation Coefficient

Significant diversification

The 3 months correlation between Dow and Bbh is 0.06. Overlapping area represents the amount of risk that can be diversified away by holding Dow Jones Industrial and Bbh Income Fund in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bbh Income Fund 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 Bbh Income. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bbh Income Fund has no effect on the direction of Dow Jones i.e., Dow Jones and Bbh Income go up and down completely randomly.
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Pair Corralation between Dow Jones and Bbh Income

Assuming the 90 days trading horizon Dow Jones Industrial is expected to under-perform the Bbh Income. In addition to that, Dow Jones is 3.13 times more volatile than Bbh Income Fund. It trades about -0.27 of its total potential returns per unit of risk. Bbh Income Fund is currently generating about -0.51 per unit of volatility. If you would invest  899.00  in Bbh Income Fund on October 7, 2024 and sell it today you would lose (22.00) from holding Bbh Income Fund or give up 2.45% of portfolio value over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthInsignificant
Accuracy95.24%
ValuesDaily Returns

Dow Jones Industrial  vs.  Bbh Income Fund

 Performance 
       Timeline  

Dow Jones and Bbh Income Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with Dow Jones and Bbh Income

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