Pair Correlation Between NZSE and EURONEXT BEL-20

This module allows you to analyze existing cross correlation between NZSE and EURONEXT BEL-20. You can compare the effects of market volatilities on NZSE and EURONEXT BEL-20 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 EURONEXT BEL-20. See also your portfolio center. Please also check ongoing floating volatility patterns of NZSE and EURONEXT BEL-20.
 Time Horizon     30 Days    Login   to change
 Performance (%) 

Pair Volatility

Assuming 30 trading days horizon, NZSE is expected to generate 0.71 times more return on investment than EURONEXT BEL-20. However, NZSE is 1.41 times less risky than EURONEXT BEL-20. It trades about 0.34 of its potential returns per unit of risk. EURONEXT BEL-20 is currently generating about 0.03 per unit of risk. If you would invest  812,531  in NZSE on February 16, 2018 and sell it today you would earn a total of  35,177  from holding NZSE or generate 4.33% return on investment over 30 days.

Correlation Coefficient

Pair Corralation between NZSE and EURONEXT BEL-20


Time Period1 Month [change]
StrengthVery Weak
ValuesDaily Returns


Excellent diversification

Overlapping area represents the amount of risk that can be diversified away by holding NZSE and EURONEXT BEL-20 in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on EURONEXT BEL-20 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 EURONEXT BEL-20. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of EURONEXT BEL-20 has no effect on the direction of NZSE i.e. NZSE and EURONEXT BEL-20 go up and down completely randomly.

Comparative Volatility

 Predicted Return Density