Pair Correlation Between IBEX 35 and Seoul Comp

This module allows you to analyze existing cross correlation between IBEX 35 and Seoul Comp. You can compare the effects of market volatilities on IBEX 35 and Seoul Comp 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 IBEX 35 with a short position of Seoul Comp. See also your portfolio center. Please also check ongoing floating volatility patterns of IBEX 35 and Seoul Comp.
 Time Horizon     30 Days    Login   to change
 IBEX 35  vs   Seoul Comp
 Performance (%) 

Pair Volatility

Assuming 30 trading days horizon, IBEX 35 is expected to generate 0.92 times more return on investment than Seoul Comp. However, IBEX 35 is 1.09 times less risky than Seoul Comp. It trades about 0.18 of its potential returns per unit of risk. Seoul Comp is currently generating about 0.1 per unit of risk. If you would invest  1,023,430  in IBEX 35 on December 19, 2017 and sell it today you would earn a total of  24,030  from holding IBEX 35 or generate 2.35% return on investment over 30 days.

Correlation Coefficient

Pair Corralation between IBEX 35 and Seoul Comp


Time Period1 Month [change]
ValuesDaily Returns


Poor diversification

Overlapping area represents the amount of risk that can be diversified away by holding IBEX 35 and Seoul Comp in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on Seoul Comp and IBEX 35 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 IBEX 35 are associated (or correlated) with Seoul Comp. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Seoul Comp has no effect on the direction of IBEX 35 i.e. IBEX 35 and Seoul Comp go up and down completely randomly.

Comparative Volatility

 Predicted Return Density