Correlation Between Dow Jones and 694308KC0

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Can any of the company-specific risk be diversified away by investing in both Dow Jones and 694308KC0 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 694308KC0 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 PCG 44 01 MAR 32, you can compare the effects of market volatilities on Dow Jones and 694308KC0 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 694308KC0. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dow Jones and 694308KC0.

Diversification Opportunities for Dow Jones and 694308KC0

0.42
  Correlation Coefficient

Very weak diversification

The 3 months correlation between Dow and 694308KC0 is 0.42. Overlapping area represents the amount of risk that can be diversified away by holding Dow Jones Industrial and PCG 44 01 MAR 32 in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PCG 44 01 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 694308KC0. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PCG 44 01 has no effect on the direction of Dow Jones i.e., Dow Jones and 694308KC0 go up and down completely randomly.
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Pair Corralation between Dow Jones and 694308KC0

Assuming the 90 days trading horizon Dow Jones Industrial is expected to generate 0.19 times more return on investment than 694308KC0. However, Dow Jones Industrial is 5.21 times less risky than 694308KC0. It trades about -0.39 of its potential returns per unit of risk. PCG 44 01 MAR 32 is currently generating about -0.25 per unit of risk. If you would invest  4,501,404  in Dow Jones Industrial on October 5, 2024 and sell it today you would lose (262,177) from holding Dow Jones Industrial or give up 5.82% of portfolio value over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthWeak
Accuracy61.9%
ValuesDaily Returns

Dow Jones Industrial  vs.  PCG 44 01 MAR 32

 Performance 
       Timeline  

Dow Jones and 694308KC0 Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with Dow Jones and 694308KC0

The main advantage of trading using opposite Dow Jones and 694308KC0 positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dow Jones position performs unexpectedly, 694308KC0 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 694308KC0 will offset losses from the drop in 694308KC0's long position.
The idea behind Dow Jones Industrial and PCG 44 01 MAR 32 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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.

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