Correlation Between Q3 All-Weather and DOW

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Can any of the company-specific risk be diversified away by investing in both Q3 All-Weather 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 Q3 All-Weather and DOW into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Q3 All-Weather Sector and DOW, you can compare the effects of market volatilities on Q3 All-Weather 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 Q3 All-Weather with a short position of DOW. Check out your portfolio center. Please also check ongoing floating volatility patterns of Q3 All-Weather and DOW.

Diversification Opportunities for Q3 All-Weather and DOW

0.9
  Correlation Coefficient

Almost no diversification

The 3 months correlation between QAWSX and DOW is 0.9. Overlapping area represents the amount of risk that can be diversified away by holding Q3 All-Weather Sector and DOW in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on DOW and Q3 All-Weather 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 Q3 All-Weather Sector 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 Q3 All-Weather i.e., Q3 All-Weather and DOW go up and down completely randomly.
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Pair Corralation between Q3 All-Weather and DOW

Assuming the 90 days horizon Q3 All-Weather Sector is expected to generate 0.66 times more return on investment than DOW. However, Q3 All-Weather Sector is 1.52 times less risky than DOW. It trades about -0.08 of its potential returns per unit of risk. DOW is currently generating about -0.11 per unit of risk. If you would invest  921.00  in Q3 All-Weather Sector on April 1, 2022 and sell it today you would lose (32.00)  from holding Q3 All-Weather Sector or give up 3.47% of portfolio value over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthVery Strong
Accuracy97.62%
ValuesDaily Returns

Q3 All-Weather Sector  vs.  DOW

 Performance (%) 
      Timeline 

Q3 All-Weather and DOW Volatility Contrast

 Predicted Return Density 
      Returns 

Q3 All-Weather Sector

Pair trading matchups for Q3 All-Weather

DOW

Pair trading matchups for DOW

Pennantpark Investme vs. DOW
Visa vs. DOW
Citigroup vs. DOW
Otp Bank vs. DOW
Brenmiller Energy vs. DOW
Ford vs. DOW
Twitter vs. DOW
Dupont Denemours vs. DOW
Salesforce vs. DOW
Cia DE vs. DOW
Alphabet 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 Q3 All-Weather and DOW

The main advantage of trading using opposite Q3 All-Weather and DOW positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Q3 All-Weather 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.

Q3 All-Weather Sector

Pair trading matchups for Q3 All-Weather

The idea behind Q3 All-Weather Sector 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

Brenmiller Energy vs. DOW
Twitter vs. DOW
Ford vs. DOW
Visa vs. DOW
Alphabet vs. DOW
Sentinelone Inc vs. DOW
Cleveland Cliffs vs. DOW
Vmware vs. DOW
Pacific Gas vs. DOW
Pennantpark Investme 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 Positions Ratings module to determine portfolio positions ratings based on digital equity recommendations. Macroaxis instant position ratings are based on combination of fundamental analysis and risk-adjusted market performance.

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