Pair Correlation Between NQFI and Stockholm

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

Pair Volatility

Assuming 30 trading days horizon, NQFI is expected to generate 0.88 times more return on investment than Stockholm. However, NQFI is 1.13 times less risky than Stockholm. It trades about 0.01 of its potential returns per unit of risk. Stockholm is currently generating about -0.2 per unit of risk. If you would invest  153,432  in NQFI on October 26, 2017 and sell it today you would earn a total of  128  from holding NQFI or generate 0.08% return on investment over 30 days.

Correlation Coefficient

Pair Corralation between NQFI and Stockholm
0.7

Parameters

Time Period1 Month [change]
DirectionPositive 
StrengthSignificant
Accuracy100.0%
ValuesDaily Returns

Diversification

Poor diversification

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

 Predicted Return Density 
      Returns