Pair Correlation Between Shanghai and NQPH

This module allows you to analyze existing cross correlation between Shanghai and NQPH. You can compare the effects of market volatilities on Shanghai and NQPH 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 Shanghai with a short position of NQPH. See also your portfolio center. Please also check ongoing floating volatility patterns of Shanghai and NQPH.
 Time Horizon     30 Days    Login   to change
Symbolsvs

Shanghai  vs.  NQPH

 Performance (%) 
      Timeline 

Pair Volatility

Assuming 30 trading days horizon, Shanghai is expected to generate 1.1 times more return on investment than NQPH. However, Shanghai is 1.1 times more volatile than NQPH. It trades about -0.1 of its potential returns per unit of risk. NQPH is currently generating about -0.25 per unit of risk. If you would invest  332,957  in Shanghai on March 27, 2018 and sell it today you would lose (21,160)  from holding Shanghai or give up 6.36% of portfolio value over 30 days.

Pair Corralation between Shanghai and NQPH

0.69
Time Period2 Months [change]
DirectionPositive 
StrengthSignificant
Accuracy83.93%
ValuesDaily Returns

Diversification

Poor diversification

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

 Predicted Return Density 
      Returns 

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ExchangeNASDAQ
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See also your portfolio center. Please also try Pattern Recognition module to use different pattern recognition models to time the market across multiple global exchanges.