Correlation Analysis Between Seoul Comp and DAX

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

Seoul Comp  vs.  DAX

 Performance (%) 

Pair Volatility

Assuming 30 trading days horizon, Seoul Comp is expected to under-perform the DAX. But the index apears to be less risky and, when comparing its historical volatility, Seoul Comp is 1.97 times less risky than DAX. The index trades about -0.14 of its potential returns per unit of risk. The DAX is currently generating about 0.0 of returns per unit of risk over similar time horizon. If you would invest  1,269,516  in DAX on June 20, 2018 and sell it today you would lose (887.00)  from holding DAX or give up 0.07% of portfolio value over 30 days.

Pair Corralation between Seoul Comp and DAX

Time Period1 Month [change]
StrengthVery Strong
ValuesDaily Returns


No risk reduction

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

Comparative Volatility

 Predicted Return Density 

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See also your portfolio center. Please also try Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.