Pair Correlation Between CAC 40 and NYSE

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

Pair Volatility

Assuming 30 trading days horizon, CAC 40 is expected to generate 0.78 times more return on investment than NYSE. However, CAC 40 is 1.29 times less risky than NYSE. It trades about -0.12 of its potential returns per unit of risk. NYSE is currently generating about -0.15 per unit of risk. If you would invest  548,121  in CAC 40 on January 25, 2018 and sell it today you would lose (16,384)  from holding CAC 40 or give up 2.99% of portfolio value over 30 days.

Correlation Coefficient

Pair Corralation between CAC 40 and NYSE
0.95

Parameters

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

Diversification

Almost no diversification

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

 Predicted Return Density 
      Returns