Pair Correlation Between BSE and Hang Seng

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

Pair Volatility

Assuming 30 trading days horizon, BSE is expected to generate 1.12 times less return on investment than Hang Seng. In addition to that, BSE is 1.02 times more volatile than Hang Seng. It trades about 0.23 of its total potential returns per unit of risk. Hang Seng is currently generating about 0.26 per unit of volatility. If you would invest  2,830,588  in Hang Seng on October 22, 2017 and sell it today you would earn a total of  95,443  from holding Hang Seng or generate 3.37% return on investment over 30 days.

Correlation Coefficient

Pair Corralation between BSE and Hang Seng


Time Period1 Month [change]
StrengthVery Weak
ValuesDaily Returns


Modest diversification

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

Comparative Volatility

 Predicted Return Density