Correlation Analysis Between DOW and IPC

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

Comparative Performance

 Predicted Return Density 

DOW  vs.  IPC

 Performance (%) 

Pair Volatility

Given the investment horizon of 30 days, DOW is expected to generate 1.19 times more return on investment than IPC. However, DOW is 1.19 times more volatile than IPC. It trades about -0.04 of its potential returns per unit of risk. IPC is currently generating about -0.23 per unit of risk. If you would invest  2,644,954  in DOW on May 17, 2019 and sell it today you would lose (37,709)  from holding DOW or give up 1.43% of portfolio value over 30 days.

Pair Corralation between DOW and IPC

Time Period2 Months [change]
ValuesDaily Returns

Diversification Opportunities for DOW and IPC

DOW diversification synergy

Very poor diversification

Overlapping area represents the amount of risk that can be diversified away by holding DOW and IPC in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on IPC and DOW 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 DOW are associated (or correlated) with IPC. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of IPC has no effect on the direction of DOW i.e. DOW and IPC go up and down completely randomly.
See also your portfolio center. Please also try Pattern Recognition module to use different pattern recognition models to time the market across multiple global exchanges.