Correlation Analysis Between NZSE and OMXVGI

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


 Performance (%) 

Pair Volatility

Assuming 30 trading days horizon, NZSE is expected to generate 1.35 times more return on investment than OMXVGI. However, NZSE is 1.35 times more volatile than OMXVGI. It trades about -0.08 of its potential returns per unit of risk. OMXVGI is currently generating about -0.37 per unit of risk. If you would invest  891,179  in NZSE on October 17, 2018 and sell it today you would lose (10,209)  from holding NZSE or give up 1.15% of portfolio value over 30 days.

Pair Corralation between NZSE and OMXVGI

Time Period1 Month [change]
ValuesDaily Returns


NZSE diversification synergy

Significant diversification

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

Comparative Volatility

 Predicted Return Density 

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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.