Pair Correlation Between XU100 and CAC 40

This module allows you to analyze existing cross correlation between XU100 and CAC 40. You can compare the effects of market volatilities on XU100 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 XU100 with a short position of CAC 40. See also your portfolio center. Please also check ongoing floating volatility patterns of XU100 and CAC 40.
 Time Horizon     30 Days    Login   to change
Symbolsvs
 XU100  vs   CAC 40
 Performance (%) 
      Timeline 

Pair Volatility

Assuming 30 trading days horizon, XU100 is expected to generate 1.05 times more return on investment than CAC 40. However, XU100 is 1.05 times more volatile than CAC 40. It trades about -0.08 of its potential returns per unit of risk. CAC 40 is currently generating about -0.17 per unit of risk. If you would invest  11,840,006  in XU100 on January 23, 2018 and sell it today you would lose (208,408)  from holding XU100 or give up 1.76% of portfolio value over 30 days.

Correlation Coefficient

Pair Corralation between XU100 and CAC 40
0.28

Parameters

Time Period1 Month [change]
DirectionPositive 
StrengthVery Weak
Accuracy81.82%
ValuesDaily Returns

Diversification

Modest diversification

Overlapping area represents the amount of risk that can be diversified away by holding XU100 and CAC 40 in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on CAC 40 and XU100 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 XU100 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 XU100 i.e. XU100 and CAC 40 go up and down completely randomly.
    Optimize

Comparative Volatility

 Predicted Return Density 
      Returns