Pair Correlation Between NZSE and Shanghai

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

Pair Volatility

Assuming 30 trading days horizon, NZSE is expected to generate 0.68 times more return on investment than Shanghai. However, NZSE is 1.47 times less risky than Shanghai. It trades about 0.01 of its potential returns per unit of risk. Shanghai is currently generating about -0.37 per unit of risk. If you would invest  831,945  in NZSE on January 25, 2018 and sell it today you would earn a total of  197.00  from holding NZSE or generate 0.02% return on investment over 30 days.

Correlation Coefficient

Pair Corralation between NZSE and Shanghai
0.11

Parameters

Time Period1 Month [change]
DirectionPositive 
StrengthInsignificant
Accuracy68.18%
ValuesDaily Returns

Diversification

Average diversification

Overlapping area represents the amount of risk that can be diversified away by holding NZSE and Shanghai in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on Shanghai and NZSE 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 NZSE 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 NZSE i.e. NZSE and Shanghai go up and down completely randomly.
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Comparative Volatility

 Predicted Return Density 
      Returns