Pair Correlation Between OMXVGI and Seoul Comp

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

Pair Volatility

Assuming 30 trading days horizon, OMXVGI is expected to generate 0.78 times more return on investment than Seoul Comp. However, OMXVGI is 1.28 times less risky than Seoul Comp. It trades about 0.36 of its potential returns per unit of risk. Seoul Comp is currently generating about 0.27 per unit of risk. If you would invest  64,907  in OMXVGI on December 24, 2017 and sell it today you would earn a total of  1,869  from holding OMXVGI or generate 2.88% return on investment over 30 days.

Correlation Coefficient

Pair Corralation between OMXVGI and Seoul Comp


Time Period1 Month [change]
ValuesDaily Returns


Very poor diversification

Overlapping area represents the amount of risk that can be diversified away by holding OMXVGI and Seoul Comp in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on Seoul Comp and OMXVGI 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 OMXVGI 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 OMXVGI i.e. OMXVGI and Seoul Comp go up and down completely randomly.

Comparative Volatility

 Predicted Return Density