Pair Correlation Between Stockholm and NQPH

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

Pair Volatility

Assuming 30 trading days horizon, Stockholm is expected to generate 1.07 times more return on investment than NQPH. However, Stockholm is 1.07 times more volatile than NQPH. It trades about -0.16 of its potential returns per unit of risk. NQPH is currently generating about -0.31 per unit of risk. If you would invest  59,505  in Stockholm on January 23, 2018 and sell it today you would lose (2,342)  from holding Stockholm or give up 3.94% of portfolio value over 30 days.

Correlation Coefficient

Pair Corralation between Stockholm and NQPH
0.79

Parameters

Time Period1 Month [change]
DirectionPositive 
StrengthSignificant
Accuracy95.24%
ValuesDaily Returns

Diversification

Poor diversification

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

 Predicted Return Density 
      Returns