Correlation Analysis Between DOW and All Ords

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

DOW  vs.  All Ords

 Performance (%) 

Pair Volatility

Given the investment horizon of 30 days, DOW is expected to under-perform the All Ords. In addition to that, DOW is 24.08 times more volatile than All Ords. It trades about -0.09 of its total potential returns per unit of risk. All Ords is currently generating about -0.71 per unit of volatility. If you would invest  632,430  in All Ords on May 23, 2018 and sell it today you would lose (220.00)  from holding All Ords or give up 0.03% of portfolio value over 30 days.

Pair Corralation between DOW and All Ords

Time Period1 Month [change]
ValuesDaily Returns


Pay attention

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

Comparative Volatility

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See also your portfolio center. Please also try Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.