This module allows you to analyze existing cross correlation between Momo and NASDAQ UK. You can compare the effects of market volatilities on Momo and NASDAQ UK 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 Momo with a short position of NASDAQ UK. See also your portfolio center. Please also check ongoing floating volatility patterns of Momo and NASDAQ UK.
|Horizon||30 Days Login to change|
Predicted Return Density
Momo Inc vs. NASDAQ UK
Given the investment horizon of 30 days, Momo is expected to generate 1.12 times less return on investment than NASDAQ UK. In addition to that, Momo is 3.04 times more volatile than NASDAQ UK. It trades about 0.06 of its total potential returns per unit of risk. NASDAQ UK is currently generating about 0.19 per unit of volatility. If you would invest 96,412 in NASDAQ UK on August 18, 2019 and sell it today you would earn a total of 1,442 from holding NASDAQ UK or generate 1.5% return on investment over 30 days.
Pair Corralation between Momo and NASDAQ UK
|Time Period||3 Months [change]|
Diversification Opportunities for Momo and NASDAQ UK
Overlapping area represents the amount of risk that can be diversified away by holding Momo Inc and NASDAQ UK in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on NASDAQ UK and Momo 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 Momo are associated (or correlated) with NASDAQ UK. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of NASDAQ UK has no effect on the direction of Momo i.e. Momo and NASDAQ UK 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.