This module allows you to analyze existing cross correlation between Straits Tms and XU100. You can compare the effects of market volatilities on Straits Tms and XU100 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 Straits Tms with a short position of XU100. See also your portfolio center. Please also check ongoing floating volatility patterns of Straits Tms and XU100.
|Horizon||30 Days Login to change|
Predicted Return Density
Straits Tms vs. XU100
Given the investment horizon of 30 days, Straits Tms is expected to generate 0.4 times more return on investment than XU100. However, Straits Tms is 2.52 times less risky than XU100. It trades about -0.16 of its potential returns per unit of risk. XU100 is currently generating about -0.14 per unit of risk. If you would invest 335,770 in Straits Tms on May 19, 2019 and sell it today you would lose (14,971) from holding Straits Tms or give up 4.46% of portfolio value over 30 days.
Pair Corralation between Straits Tms and XU100
|Time Period||2 Months [change]|
Diversification Opportunities for Straits Tms and XU100
Overlapping area represents the amount of risk that can be diversified away by holding Straits Tms and XU100 in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on XU100 and Straits Tms 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 Straits Tms are associated (or correlated) with XU100. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of XU100 has no effect on the direction of Straits Tms i.e. Straits Tms and XU100 go up and down completely randomly.
See also your portfolio center. Please also try Headlines Timeline module to stay connected to all market stories and filter out noise. drill down to analyze hype elasticity.