Correlation Analysis Between ATX and NZSE

This module allows you to analyze existing cross correlation between ATX and NZSE. You can compare the effects of market volatilities on ATX and NZSE 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 ATX with a short position of NZSE. See also your portfolio center. Please also check ongoing floating volatility patterns of ATX and NZSE.
Horizon     30 Days    Login   to change

ATX  vs.  NZSE

 Performance (%) 

Pair Volatility

Given the investment horizon of 30 days, ATX is expected to generate 1.32 times less return on investment than NZSE. In addition to that, ATX is 1.04 times more volatile than NZSE. It trades about 0.12 of its total potential returns per unit of risk. NZSE is currently generating about 0.17 per unit of volatility. If you would invest  910,915  in NZSE on August 20, 2018 and sell it today you would earn a total of  23,591  from holding NZSE or generate 2.59% return on investment over 30 days.

Pair Corralation between ATX and NZSE

Time Period1 Month [change]
ValuesDaily Returns


Poor diversification

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

Comparative Volatility

 Predicted Return Density 

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See also your portfolio center. Please also try Price Transformation module to use price transformation models to analyze depth of different equity instruments across global markets.