Pair Correlation Between NYSE and Hang Seng

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

Pair Volatility

Given the investment horizon of 30 days, NYSE is expected to generate 0.82 times more return on investment than Hang Seng. However, NYSE is 1.22 times less risky than Hang Seng. It trades about -0.18 of its potential returns per unit of risk. Hang Seng is currently generating about -0.16 per unit of risk. If you would invest  1,363,702  in NYSE on January 26, 2018 and sell it today you would lose (75,291)  from holding NYSE or give up 5.52% of portfolio value over 30 days.

Correlation Coefficient

Pair Corralation between NYSE and Hang Seng
0.52

Parameters

Time Period1 Month [change]
DirectionPositive 
StrengthWeak
Accuracy90.91%
ValuesDaily Returns

Diversification

Very weak diversification

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

 Predicted Return Density 
      Returns