Pair Correlation Between OSE All and OMXRGI

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

Pair Volatility

Assuming 30 trading days horizon, OSE All is expected to generate 1.05 times more return on investment than OMXRGI. However, OSE All is 1.05 times more volatile than OMXRGI. It trades about -0.02 of its potential returns per unit of risk. OMXRGI is currently generating about -0.06 per unit of risk. If you would invest  92,555  in OSE All on January 26, 2018 and sell it today you would lose (496.00)  from holding OSE All or give up 0.54% of portfolio value over 30 days.

Correlation Coefficient

Pair Corralation between OSE All and OMXRGI
0.54

Parameters

Time Period1 Month [change]
DirectionPositive 
StrengthWeak
Accuracy91.3%
ValuesDaily Returns

Diversification

Very weak diversification

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

Comparative Volatility

 Predicted Return Density 
      Returns