Pair Correlation Between EURONEXT BEL-20 and BSE

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

Pair Volatility

Given the investment horizon of 30 days, EURONEXT BEL-20 is expected to generate 1.41 times more return on investment than BSE. However, EURONEXT BEL-20 is 1.41 times more volatile than BSE. It trades about -0.19 of its potential returns per unit of risk. BSE is currently generating about -0.34 per unit of risk. If you would invest  416,201  in EURONEXT BEL-20 on January 26, 2018 and sell it today you would lose (19,579)  from holding EURONEXT BEL-20 or give up 4.7% of portfolio value over 30 days.

Correlation Coefficient

Pair Corralation between EURONEXT BEL-20 and BSE


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 BSE in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on BSE 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 BSE. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BSE has no effect on the direction of EURONEXT BEL-20 i.e. EURONEXT BEL-20 and BSE go up and down completely randomly.

Comparative Volatility

 Predicted Return Density