Correlation Analysis Between NZSE and Shanghai

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

NZSE  vs.  Shanghai

 Performance (%) 

Pair Volatility

Assuming 30 trading days horizon, NZSE is expected to under-perform the Shanghai. But the index apears to be less risky and, when comparing its historical volatility, NZSE is 1.95 times less risky than Shanghai. The index trades about -0.04 of its potential returns per unit of risk. The Shanghai is currently generating about 0.03 of returns per unit of risk over similar time horizon. If you would invest  257,008  in Shanghai on November 12, 2018 and sell it today you would earn a total of  3,207  from holding Shanghai or generate 1.25% return on investment over 30 days.

Pair Corralation between NZSE and Shanghai

Time Period2 Months [change]
ValuesDaily Returns


NZSE diversification synergy

Poor diversification

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

Comparative Volatility

 Predicted Return Density 

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See also your portfolio center. Please also try Portfolio Diagnostics module to use generated alerts and portfolio events aggregator to diagnose current holdings.