Correlation Analysis Between OMXVGI and IPC

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

OMXVGI  vs.  IPC

 Performance (%) 
      Timeline 

Pair Volatility

Assuming 30 trading days horizon, OMXVGI is expected to generate 11.36 times less return on investment than IPC. But when comparing it to its historical volatility, OMXVGI is 3.25 times less risky than IPC. It trades about 0.06 of its potential returns per unit of risk. IPC is currently generating about 0.22 of returns per unit of risk over similar time horizon. If you would invest  4,675,941  in IPC on June 20, 2018 and sell it today you would earn a total of  198,838  from holding IPC or generate 4.25% return on investment over 30 days.

Pair Corralation between OMXVGI and IPC

0.33
Time Period1 Month [change]
DirectionPositive 
StrengthVery Weak
Accuracy100.0%
ValuesDaily Returns

Diversification

Weak diversification

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

 Predicted Return Density 
      Returns 

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