Pair Correlation Between NYSE and Stockholm

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

Pair Volatility

Given the investment horizon of 30 days, NYSE is expected to generate 0.54 times more return on investment than Stockholm. However, NYSE is 1.84 times less risky than Stockholm. It trades about -0.11 of its potential returns per unit of risk. Stockholm is currently generating about -0.22 per unit of risk. If you would invest  1,238,442  in NYSE on October 21, 2017 and sell it today you would lose (8,152)  from holding NYSE or give up 0.66% of portfolio value over 30 days.

Correlation Coefficient

Pair Corralation between NYSE and Stockholm
0.73

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 NYSE and Stockholm in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on Stockholm and NYSE 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 NYSE 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 NYSE i.e. NYSE and Stockholm go up and down completely randomly.
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Comparative Volatility

 Predicted Return Density 
      Returns