Correlation Analysis Between ISEQ and DOW

This module allows you to analyze existing cross correlation between ISEQ and DOW. You can compare the effects of market volatilities on ISEQ and DOW 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 ISEQ with a short position of DOW. See also your portfolio center. Please also check ongoing floating volatility patterns of ISEQ and DOW.
Horizon     30 Days    Login   to change
Check Efficiency

Comparative Performance

ISEQ  vs.  DOW

 Performance (%) 

Pair Volatility

Assuming 30 trading days horizon, ISEQ is expected to under-perform the DOW. In addition to that, ISEQ is 1.18 times more volatile than DOW. It trades about -0.18 of its total potential returns per unit of risk. DOW is currently generating about -0.05 per unit of volatility. If you would invest  2,655,954  in DOW on May 18, 2019 and sell it today you would lose (48,709)  from holding DOW or give up 1.83% of portfolio value over 30 days.

Pair Corralation between ISEQ and DOW

Time Period2 Months [change]
ValuesDaily Returns

Diversification Opportunities for ISEQ and DOW

ISEQ diversification synergy

Pay attention

Overlapping area represents the amount of risk that can be diversified away by holding ISEQ and DOW in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on DOW and ISEQ 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 ISEQ are associated (or correlated) with DOW. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of DOW has no effect on the direction of ISEQ i.e. ISEQ and DOW go up and down completely randomly.
See also your portfolio center. Please also try Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.