Pair Correlation Between Stockholm and NQTH

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

Pair Volatility

Assuming 30 trading days horizon, Stockholm is expected to under-perform the NQTH. But the index apears to be less risky and, when comparing its historical volatility, Stockholm is 1.12 times less risky than NQTH. The index trades about -0.14 of its potential returns per unit of risk. The NQTH is currently generating about 0.22 of returns per unit of risk over similar time horizon. If you would invest  112,910  in NQTH on October 24, 2017 and sell it today you would earn a total of  3,264  from holding NQTH or generate 2.89% return on investment over 30 days.

Correlation Coefficient

Pair Corralation between Stockholm and NQTH


Time Period1 Month [change]
ValuesDaily Returns


Pay attention

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

Comparative Volatility