Correlation Analysis Between NZSE and Seoul Comp

This module allows you to analyze existing cross correlation between NZSE and Seoul Comp. You can compare the effects of market volatilities on NZSE and Seoul Comp 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 Seoul Comp. See also your portfolio center. Please also check ongoing floating volatility patterns of NZSE and Seoul Comp.
Horizon     30 Days    Login   to change
Symbolsvs

NZSE  vs.  Seoul Comp

 Performance (%) 
      Timeline 

Pair Volatility

Assuming 30 trading days horizon, NZSE is expected to generate 0.86 times more return on investment than Seoul Comp. However, NZSE is 1.16 times less risky than Seoul Comp. It trades about -0.26 of its potential returns per unit of risk. Seoul Comp is currently generating about -0.34 per unit of risk. If you would invest  937,597  in NZSE on September 21, 2018 and sell it today you would lose (50,417)  from holding NZSE or give up 5.38% of portfolio value over 30 days.

Pair Corralation between NZSE and Seoul Comp

0.94
Time Period1 Month [change]
DirectionPositive 
StrengthVery Strong
Accuracy100.0%
ValuesDaily Returns

Diversification

Almost no diversification

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

 Predicted Return Density 
      Returns 

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