Pair Correlation Between FTSE MIB and All Ords

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

Pair Volatility

Assuming 30 trading days horizon, FTSE MIB is expected to generate 2.61 times more return on investment than All Ords. However, FTSE MIB is 2.61 times more volatile than All Ords. It trades about 0.3 of its potential returns per unit of risk. All Ords is currently generating about 0.09 per unit of risk. If you would invest  2,239,053  in FTSE MIB on December 18, 2017 and sell it today you would earn a total of  103,930  from holding FTSE MIB or generate 4.64% return on investment over 30 days.

Correlation Coefficient

Pair Corralation between FTSE MIB and All Ords


Time Period1 Month [change]
ValuesDaily Returns


Significant diversification

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

Comparative Volatility

 Predicted Return Density