Pair Correlation Between NQPH and Swiss Mrt

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

Pair Volatility

Assuming 30 trading days horizon, NQPH is expected to under-perform the Swiss Mrt. But the index apears to be less risky and, when comparing its historical volatility, NQPH is 1.01 times less risky than Swiss Mrt. The index trades about -0.42 of its potential returns per unit of risk. The Swiss Mrt is currently generating about -0.25 of returns per unit of risk over similar time horizon. If you would invest  948,296  in Swiss Mrt on January 25, 2018 and sell it today you would lose (53,477)  from holding Swiss Mrt or give up 5.64% of portfolio value over 30 days.

Correlation Coefficient

Pair Corralation between NQPH and Swiss Mrt


Time Period1 Month [change]
ValuesDaily Returns


Pay attention

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

Comparative Volatility