Pair Correlation Between Shanghai and NQEGT

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

Pair Volatility

Assuming 30 trading days horizon, Shanghai is expected to generate 37.31 times less return on investment than NQEGT. But when comparing it to its historical volatility, Shanghai is 1.29 times less risky than NQEGT. It trades about 0.02 of its potential returns per unit of risk. NQEGT is currently generating about 0.66 of returns per unit of risk over similar time horizon. If you would invest  115,321  in NQEGT on February 20, 2018 and sell it today you would earn a total of  15,752  from holding NQEGT or generate 13.66% return on investment over 30 days.

Correlation Coefficient

Pair Corralation between Shanghai and NQEGT


Time Period1 Month [change]
ValuesDaily Returns


Very weak diversification

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

Comparative Volatility

 Predicted Return Density