Pair Correlation Between OMXRGI and DOW

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

Pair Volatility

Assuming 30 trading days horizon, OMXRGI is expected to generate 1.01 times more return on investment than DOW. However, OMXRGI is 1.01 times more volatile than DOW. It trades about 0.18 of its potential returns per unit of risk. DOW is currently generating about 0.08 per unit of risk. If you would invest  102,042  in OMXRGI on October 24, 2017 and sell it today you would earn a total of  1,353  from holding OMXRGI or generate 1.33% return on investment over 30 days.

Correlation Coefficient

Pair Corralation between OMXRGI and DOW
0.11

Parameters

Time Period1 Month [change]
DirectionPositive 
StrengthInsignificant
Accuracy95.45%
ValuesDaily Returns

Diversification

Average diversification

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

 Predicted Return Density 
      Returns