Correlation Between Dunham Monthly and DOW

By analyzing existing cross correlation between Dunham Monthly Distribution and DOW, you can compare the effects of market volatilities on Dunham Monthly and DOW 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 Dunham Monthly with a short position of DOW. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dunham Monthly and DOW.

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Can any of the company-specific risk be diversified away by investing in both Dunham Monthly and DOW 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 Dunham Monthly and DOW into the same portfolio, which is an essential part of the fundamental portfolio management process.

Diversification Opportunities for Dunham Monthly and DOW

-0.64
  Correlation Coefficient
Dunham Monthly Distr
DOW

Excellent diversification

The 3 months correlation between Dunham and DOW is -0.64. Overlapping area represents the amount of risk that can be diversified away by holding Dunham Monthly Distribution and DOW in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on DOW and Dunham Monthly 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 Dunham Monthly Distribution are associated (or correlated) with DOW. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of DOW has no effect on the direction of Dunham Monthly i.e., Dunham Monthly and DOW go up and down completely randomly.
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Pair Corralation between Dunham Monthly and DOW

Assuming the 90 days horizon Dunham Monthly Distribution is expected to generate 0.39 times more return on investment than DOW. However, Dunham Monthly Distribution is 2.55 times less risky than DOW. It trades about -0.2 of its potential returns per unit of risk. DOW is currently generating about -0.24 per unit of risk. If you would invest  3,220  in Dunham Monthly Distribution on September 1, 2021 and sell it today you would lose (41.00)  from holding Dunham Monthly Distribution or give up 1.27% of portfolio value over 90 days.
Time Period3 Months [change]
DirectionMoves Against 
StrengthWeak
Accuracy100.0%
ValuesDaily Returns

Dunham Monthly Distribution  vs.  DOW

 Performance (%) 
      Timeline 

Dunham Monthly and DOW Volatility Contrast

 Predicted Return Density 
      Returns 

Dunham Monthly Distribution

Pair trading matchups for Dunham Monthly

DOW

Pair trading matchups for DOW

GM vs. DOW
Microsoft Corp vs. DOW
Bitcoin vs. DOW
Arcbest Corp vs. DOW
BriaCell Therapeutics vs. DOW
Smart Bitcoin vs. DOW
Enovix Corp vs. DOW
Plug Power vs. DOW
Du Pont vs. DOW
Calumet Specialty vs. DOW
The effect of pair diversification on risk is to reduce it, but we should note this doesn't apply to all risk types. When we trade pairs against DOW as a counterpart, there is always some inherent risk that will never be diversified away no matter what. This volatility limits the effect of tactical diversification using pair trading. DOW's systematic risk is the inherent uncertainty of the entire market, and therefore cannot be mitigated even by pair-trading it against the equity that is not highly correlated to it. On the other hand, DOW's unsystematic risk describes the types of risk that we can protect against, at least to some degree, by selecting a matching pair that is not perfectly correlated to DOW.

Pair Trading with Dunham Monthly and DOW

The main advantage of trading using opposite Dunham Monthly and DOW positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dunham Monthly position performs unexpectedly, DOW 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 DOW will offset losses from the drop in DOW's long position.

Dunham Monthly Distribution

Pair trading matchups for Dunham Monthly

The idea behind Dunham Monthly Distribution and DOW 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.

DOW

Pair trading matchups for DOW

Arcbest Corp vs. DOW
Ford vs. DOW
Plug Power vs. DOW
Smart Bitcoin vs. DOW
Bitcoin vs. DOW
Calumet Specialty vs. DOW
Bitcoin Cash vs. DOW
Du Pont vs. DOW
BriaCell Therapeutics vs. DOW
Tesla vs. DOW
Bitcoin SV vs. DOW
Salesforce vs. DOW
The effect of pair diversification on risk is to reduce it, but we should note this doesn't apply to all risk types. When we trade pairs against DOW as a counterpart, there is always some inherent risk that will never be diversified away no matter what. This volatility limits the effect of tactical diversification using pair trading. DOW's systematic risk is the inherent uncertainty of the entire market, and therefore cannot be mitigated even by pair-trading it against the equity that is not highly correlated to it. On the other hand, DOW's unsystematic risk describes the types of risk that we can protect against, at least to some degree, by selecting a matching pair that is not perfectly correlated to DOW.
Check out your portfolio center. 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.

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