Pair Correlation Between XU100 and FTSE MIB

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

Pair Volatility

Assuming 30 trading days horizon, XU100 is expected to generate 1.93 times more return on investment than FTSE MIB. However, XU100 is 1.93 times more volatile than FTSE MIB. It trades about -0.03 of its potential returns per unit of risk. FTSE MIB is currently generating about -0.1 per unit of risk. If you would invest  10,730,325  in XU100 on October 21, 2017 and sell it today you would lose (106,379)  from holding XU100 or give up 0.99% of portfolio value over 30 days.

Correlation Coefficient

Pair Corralation between XU100 and FTSE MIB
0.81

Parameters

Time Period1 Month [change]
DirectionPositive 
StrengthStrong
Accuracy90.48%
ValuesDaily Returns

Diversification

Very poor diversification

Overlapping area represents the amount of risk that can be diversified away by holding XU100 and FTSE MIB in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on FTSE MIB 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 FTSE MIB. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of FTSE MIB has no effect on the direction of XU100 i.e. XU100 and FTSE MIB go up and down completely randomly.
    Optimize

Comparative Volatility

 Predicted Return Density 
      Returns