This module allows you to analyze existing cross correlation between NQEGT and Russell 2000 . You can compare the effects of market volatilities on NQEGT and Russell 2000 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 NQEGT with a short position of Russell 2000. See also your portfolio center. Please also check ongoing floating volatility patterns of NQEGT and Russell 2000.
|Horizon||30 Days Login to change|
Predicted Return Density
NQEGT vs. Russell 2000
Assuming 30 trading days horizon, NQEGT is expected to under-perform the Russell 2000. In addition to that, NQEGT is 1.88 times more volatile than Russell 2000 . It trades about -0.04 of its total potential returns per unit of risk. Russell 2000 is currently generating about -0.01 per unit of volatility. If you would invest 155,562 in Russell 2000 on September 16, 2019 and sell it today you would lose (3,232) from holding Russell 2000 or give up 2.08% of portfolio value over 30 days.
Pair Corralation between NQEGT and Russell 2000
|Time Period||3 Months [change]|
Diversification Opportunities for NQEGT and Russell 2000
Overlapping area represents the amount of risk that can be diversified away by holding NQEGT and Russell 2000 in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on Russell 2000 and NQEGT 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 NQEGT are associated (or correlated) with Russell 2000. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Russell 2000 has no effect on the direction of NQEGT i.e. NQEGT and Russell 2000 go up and down completely randomly.
See also your portfolio center. Please also try Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.