This module allows you to analyze existing cross correlation between Citigroup and NQFI. You can compare the effects of market volatilities on Citigroup and NQFI 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 Citigroup with a short position of NQFI. See also your portfolio center. Please also check ongoing floating volatility patterns of Citigroup and NQFI.
|Horizon||30 Days Login to change|
Predicted Return Density
Citigroup Inc vs. NQFI
Taking into account the 30 trading days horizon, Citigroup is expected to generate 1.61 times more return on investment than NQFI. However, Citigroup is 1.61 times more volatile than NQFI. It trades about 0.11 of its potential returns per unit of risk. NQFI is currently generating about -0.18 per unit of risk. If you would invest 6,033 in Citigroup on April 24, 2019 and sell it today you would earn a total of 411.00 from holding Citigroup or generate 6.81% return on investment over 30 days.
Pair Corralation between Citigroup and NQFI
|Time Period||2 Months [change]|
Diversification Opportunities for Citigroup and NQFI
Overlapping area represents the amount of risk that can be diversified away by holding Citigroup Inc and NQFI in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on NQFI and Citigroup 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 Citigroup are associated (or correlated) with NQFI. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of NQFI has no effect on the direction of Citigroup i.e. Citigroup and NQFI go up and down completely randomly.
See also your portfolio center. Please also try Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.