Pair Correlation Between Shanghai and NZSE

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

Pair Volatility

Assuming 30 trading days horizon, Shanghai is expected to generate 1.02 times more return on investment than NZSE. However, Shanghai is 1.02 times more volatile than NZSE. It trades about 0.04 of its potential returns per unit of risk. NZSE is currently generating about -0.09 per unit of risk. If you would invest  337,017  in Shanghai on October 19, 2017 and sell it today you would earn a total of  1,274  from holding Shanghai or generate 0.38% return on investment over 30 days.

Correlation Coefficient

Pair Corralation between Shanghai and NZSE
-0.72

Parameters

Time Period1 Month [change]
DirectionNegative 
StrengthWeak
Accuracy95.45%
ValuesDaily Returns

Diversification

Pay attention

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

 Predicted Return Density 
      Returns