Pair Correlation Between Shanghai and All Ords

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

Pair Volatility

Assuming 30 trading days horizon, Shanghai is expected to under-perform the All Ords. In addition to that, Shanghai is 1.82 times more volatile than All Ords. It trades about -0.13 of its total potential returns per unit of risk. All Ords is currently generating about -0.02 per unit of volatility. If you would invest  606,390  in All Ords on February 22, 2018 and sell it today you would lose (2,070)  from holding All Ords or give up 0.34% of portfolio value over 30 days.

Correlation Coefficient

Pair Corralation between Shanghai and All Ords


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 All Ords in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on All Ords 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 All Ords. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of All Ords has no effect on the direction of Shanghai i.e. Shanghai and All Ords go up and down completely randomly.

Comparative Volatility

 Predicted Return Density