Pair Correlation Between SP 500 and NZSE

This module allows you to analyze existing cross correlation between S&P 500 and NZSE. You can compare the effects of market volatilities on SP 500 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 SP 500 with a short position of NZSE. See also your portfolio center. Please also check ongoing floating volatility patterns of SP 500 and NZSE.
Investment Horizon     30 Days    Login   to change
Symbolsvs
 S&P 500  vs   NZSE
 Performance (%) 
      Timeline 

Pair Volatility

Assuming 30 trading days horizon, S&P 500 is expected to generate 0.85 times more return on investment than NZSE. However, S&P 500 is 1.18 times less risky than NZSE. It trades about 0.08 of its potential returns per unit of risk. NZSE is currently generating about -0.1 per unit of risk. If you would invest  256,498  in S&P 500 on October 21, 2017 and sell it today you would earn a total of  1,387  from holding S&P 500 or generate 0.54% return on investment over 30 days.

Correlation Coefficient

Pair Corralation between SP 500 and NZSE
-0.48

Parameters

Time Period1 Month [change]
DirectionNegative 
StrengthVery Weak
Accuracy95.24%
ValuesDaily Returns

Diversification

Very good diversification

Overlapping area represents the amount of risk that can be diversified away by holding S&P 500 and NZSE in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on NZSE and SP 500 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 S&P 500 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 SP 500 i.e. SP 500 and NZSE go up and down completely randomly.
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Comparative Volatility

 Predicted Return Density 
      Returns