Correlation Analysis Between Nasdaq and BSE

This module allows you to analyze existing cross correlation between Nasdaq and BSE. You can compare the effects of market volatilities on Nasdaq and BSE 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 Nasdaq with a short position of BSE. See also your portfolio center. Please also check ongoing floating volatility patterns of Nasdaq and BSE.
Horizon     30 Days    Login   to change

Nasdaq  vs.  BSE

 Performance (%) 

Pair Volatility

Assuming 30 trading days horizon, Nasdaq is expected to under-perform the BSE. In addition to that, Nasdaq is 1.7 times more volatile than BSE. It trades about -0.08 of its total potential returns per unit of risk. BSE is currently generating about 0.04 per unit of volatility. If you would invest  3,473,358  in BSE on November 11, 2018 and sell it today you would earn a total of  41,643  from holding BSE or generate 1.2% return on investment over 30 days.

Pair Corralation between Nasdaq and BSE

Time Period2 Months [change]
ValuesDaily Returns


Nasdaq diversification synergy

Good diversification

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

Comparative Volatility

 Predicted Return Density 

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See also your portfolio center. Please also try Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.