Pair Correlation Between EURONEXT BEL-20 and NYSE

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

Pair Volatility

Given the investment horizon of 30 days, EURONEXT BEL-20 is expected to under-perform the NYSE. In addition to that, EURONEXT BEL-20 is 1.88 times more volatile than NYSE. It trades about -0.3 of its total potential returns per unit of risk. NYSE is currently generating about -0.11 per unit of volatility. If you would invest  1,238,442  in NYSE on October 21, 2017 and sell it today you would lose (8,152)  from holding NYSE or give up 0.66% of portfolio value over 30 days.

Correlation Coefficient

Pair Corralation between EURONEXT BEL-20 and NYSE


Time Period1 Month [change]
ValuesDaily Returns


Very poor diversification

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

Comparative Volatility

 Predicted Return Density