This module allows you to analyze existing cross correlation between DAX and Jakarta Comp. You can compare the effects of market volatilities on DAX and Jakarta 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 DAX with a short position of Jakarta Comp. See also your portfolio center. Please also check ongoing floating volatility patterns of DAX and Jakarta Comp.
|Horizon||30 Days Login to change|
Predicted Return Density
DAX vs. Jakarta Comp
Assuming 30 trading days horizon, DAX is expected to generate 1.86 times more return on investment than Jakarta Comp. However, DAX is 1.86 times more volatile than Jakarta Comp. It trades about 0.02 of its potential returns per unit of risk. Jakarta Comp is currently generating about -0.1 per unit of risk. If you would invest 1,238,734 in DAX on September 13, 2019 and sell it today you would earn a total of 12,431 from holding DAX or generate 1.0% return on investment over 30 days.
Pair Corralation between DAX and Jakarta Comp
|Time Period||3 Months [change]|
Diversification Opportunities for DAX and Jakarta Comp
Very good diversification
Overlapping area represents the amount of risk that can be diversified away by holding DAX and Jakarta Comp in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on Jakarta Comp and DAX 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 DAX are associated (or correlated) with Jakarta Comp. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Jakarta Comp has no effect on the direction of DAX i.e. DAX and Jakarta Comp go up and down completely randomly.
See also your portfolio center. Please also try Price Transformation module to use price transformation models to analyze depth of different equity instruments across global markets.