Pair Correlation Between NYSE and CAC 40

This module allows you to analyze existing cross correlation between NYSE and CAC 40. You can compare the effects of market volatilities on NYSE and CAC 40 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 CAC 40. See also your portfolio center. Please also check ongoing floating volatility patterns of NYSE and CAC 40.
Investment Horizon     30 Days    Login   to change
Symbolsvs
 NYSE  vs   CAC 40
 Performance (%) 
      Timeline 

Pair Volatility

Given the investment horizon of 30 days, NYSE is expected to generate 0.6 times more return on investment than CAC 40. However, NYSE is 1.66 times less risky than CAC 40. It trades about 0.05 of its potential returns per unit of risk. CAC 40 is currently generating about -0.11 per unit of risk. If you would invest  1,235,243  in NYSE on October 26, 2017 and sell it today you would earn a total of  3,840  from holding NYSE or generate 0.31% return on investment over 30 days.

Correlation Coefficient

Pair Corralation between NYSE and CAC 40
0.5

Parameters

Time Period1 Month [change]
DirectionPositive 
StrengthWeak
Accuracy95.45%
ValuesDaily Returns

Diversification

Very weak diversification

Overlapping area represents the amount of risk that can be diversified away by holding NYSE and CAC 40 in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on CAC 40 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 CAC 40. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CAC 40 has no effect on the direction of NYSE i.e. NYSE and CAC 40 go up and down completely randomly.
    Optimize

Comparative Volatility

 Predicted Return Density 
      Returns