Pair Correlation Between Seoul Comp and Bovespa

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

Pair Volatility

Assuming 30 trading days horizon, Seoul Comp is expected to generate 0.34 times more return on investment than Bovespa. However, Seoul Comp is 2.98 times less risky than Bovespa. It trades about 0.15 of its potential returns per unit of risk. Bovespa is currently generating about -0.09 per unit of risk. If you would invest  249,005  in Seoul Comp on October 23, 2017 and sell it today you would earn a total of  3,762  from holding Seoul Comp or generate 1.51% return on investment over 30 days.

Correlation Coefficient

Pair Corralation between Seoul Comp and Bovespa


Time Period1 Month [change]
ValuesDaily Returns


Very good diversification

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

Comparative Volatility

 Predicted Return Density