Correlation Analysis Between DOW and SPTSX Comp

This module allows you to analyze existing cross correlation between DOW and SPTSX Comp. You can compare the effects of market volatilities on DOW and SPTSX Comp 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 SPTSX Comp. See also your portfolio center. Please also check ongoing floating volatility patterns of DOW and SPTSX Comp.
 Time Horizon     30 Days    Login   to change
Symbolsvs

DOW  vs.  SPTSX Comp

 Performance (%) 
      Timeline 

Pair Volatility

Given the investment horizon of 30 days, DOW is expected to under-perform the SPTSX Comp. In addition to that, DOW is 1.83 times more volatile than SPTSX Comp. It trades about -0.05 of its total potential returns per unit of risk. SPTSX Comp is currently generating about 0.19 per unit of volatility. If you would invest  1,613,380  in SPTSX Comp on May 23, 2018 and sell it today you would earn a total of  31,039  from holding SPTSX Comp or generate 1.92% return on investment over 30 days.

Pair Corralation between DOW and SPTSX Comp

0.0
Time Period1 Month [change]
DirectionFlat 
StrengthInsignificant
Accuracy100.0%
ValuesDaily Returns

Diversification

Pay attention

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

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