Pair Correlation Between NQTH and Bovespa

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

Pair Volatility

Assuming 30 trading days horizon, NQTH is expected to generate 0.44 times more return on investment than Bovespa. However, NQTH is 2.26 times less risky than Bovespa. It trades about 0.2 of its potential returns per unit of risk. Bovespa is currently generating about -0.09 per unit of risk. If you would invest  112,403  in NQTH on October 21, 2017 and sell it today you would earn a total of  2,755  from holding NQTH or generate 2.45% return on investment over 30 days.

Correlation Coefficient

Pair Corralation between NQTH and Bovespa
-0.25

Parameters

Time Period1 Month [change]
DirectionNegative 
StrengthInsignificant
Accuracy100.0%
ValuesDaily Returns

Diversification

Very good diversification

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

 Predicted Return Density 
      Returns