Pair Correlation Between Stockholm and Shanghai

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

Pair Volatility

Assuming 30 trading days horizon, Stockholm is expected to generate 0.95 times more return on investment than Shanghai. However, Stockholm is 1.06 times less risky than Shanghai. It trades about -0.15 of its potential returns per unit of risk. Shanghai is currently generating about -0.47 per unit of risk. If you would invest  59,226  in Stockholm on January 22, 2018 and sell it today you would lose (2,176)  from holding Stockholm or give up 3.67% of portfolio value over 30 days.

Correlation Coefficient

Pair Corralation between Stockholm and Shanghai


Time Period1 Month [change]
ValuesDaily Returns


Significant diversification

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

Comparative Volatility

 Predicted Return Density