Correlation Analysis Between DOW and First Trust

This module allows you to analyze existing cross correlation between DOW and First Trust South Korea AlphaDEX ETF. You can compare the effects of market volatilities on DOW and First Trust 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 with a short position of First Trust. See also your portfolio center. Please also check ongoing floating volatility patterns of DOW and First Trust.
 Time Horizon     30 Days    Login   to change
Symbolsvs

DOW  vs.  First Trust South Korea AlphaD

 Performance (%) 
      Timeline 

Pair Volatility

If you would invest  2,498,747  in DOW on June 18, 2018 and sell it today you would earn a total of  19,878  from holding DOW or generate 0.8% return on investment over 30 days.

Pair Corralation between DOW and First Trust

0.59
Time Period1 Month [change]
DirectionPositive 
StrengthWeak
Accuracy3.45%
ValuesDaily Returns

Diversification

Very weak diversification

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

 Predicted Return Density 
      Returns 

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See also your portfolio center. Please also try Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.