Pair Correlation Between NYSE and Bovespa

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

Pair Volatility

Given the investment horizon of 30 days, NYSE is expected to generate 0.21 times more return on investment than Bovespa. However, NYSE is 4.82 times less risky than Bovespa. It trades about -0.16 of its potential returns per unit of risk. Bovespa is currently generating about -0.13 per unit of risk. If you would invest  1,243,053  in NYSE on October 20, 2017 and sell it today you would lose (12,763)  from holding NYSE or give up 1.03% of portfolio value over 30 days.

Correlation Coefficient

Pair Corralation between NYSE and Bovespa
0.66

Parameters

Time Period1 Month [change]
DirectionPositive 
StrengthSignificant
Accuracy95.45%
ValuesDaily Returns

Diversification

Poor diversification

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

 Predicted Return Density 
      Returns