Pair Correlation Between BSE and OMX COPENHAGEN

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

Pair Volatility

Assuming 30 trading days horizon, BSE is expected to under-perform the OMX COPENHAGEN. In addition to that, BSE is 1.01 times more volatile than OMX COPENHAGEN. It trades about -0.17 of its total potential returns per unit of risk. OMX COPENHAGEN is currently generating about 0.09 per unit of volatility. If you would invest  132,157  in OMX COPENHAGEN on February 15, 2018 and sell it today you would earn a total of  2,140  from holding OMX COPENHAGEN or generate 1.62% return on investment over 30 days.

Correlation Coefficient

Pair Corralation between BSE and OMX COPENHAGEN


Time Period1 Month [change]
ValuesDaily Returns


Poor diversification

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

Comparative Volatility

 Predicted Return Density