This module allows you to analyze existing cross correlation between Shanghai and Seoul Comp. You can compare the effects of market volatilities on Shanghai and Seoul Comp 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 Shanghai with a short position of Seoul Comp. See also your portfolio center. Please also check ongoing floating volatility patterns of Shanghai and Seoul Comp.
|Horizon||30 Days Login to change|
Predicted Return Density
Shanghai vs. Seoul Comp
Assuming 30 trading days horizon, Shanghai is expected to under-perform the Seoul Comp. In addition to that, Shanghai is 1.79 times more volatile than Seoul Comp. It trades about -0.2 of its total potential returns per unit of risk. Seoul Comp is currently generating about -0.21 per unit of volatility. If you would invest 224,589 in Seoul Comp on May 17, 2019 and sell it today you would lose (15,048) from holding Seoul Comp or give up 6.7% of portfolio value over 30 days.
Pair Corralation between Shanghai and Seoul Comp
|Time Period||2 Months [change]|
Diversification Opportunities for Shanghai and Seoul Comp
Very poor diversification
Overlapping area represents the amount of risk that can be diversified away by holding Shanghai and Seoul Comp in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on Seoul Comp and Shanghai 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 Shanghai are associated (or correlated) with Seoul Comp. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Seoul Comp has no effect on the direction of Shanghai i.e. Shanghai and Seoul Comp go up and down completely randomly.
See also your portfolio center. Please also try Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.