Pair Correlation Between BSE and Seoul Comp

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

Pair Volatility

Assuming 30 trading days horizon, BSE is expected to generate 1.26 times more return on investment than Seoul Comp. However, BSE is 1.26 times more volatile than Seoul Comp. It trades about 0.21 of its potential returns per unit of risk. Seoul Comp is currently generating about 0.2 per unit of risk. If you would invest  3,260,734  in BSE on October 24, 2017 and sell it today you would earn a total of  90,006  from holding BSE or generate 2.76% return on investment over 30 days.

Correlation Coefficient

Pair Corralation between BSE and Seoul Comp
0.62

Parameters

Time Period1 Month [change]
DirectionPositive 
StrengthSignificant
Accuracy100.0%
ValuesDaily Returns

Diversification

Poor diversification

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

Comparative Volatility

 Predicted Return Density 
      Returns