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This module allows you to analyze existing cross correlation between Russell 2000 and Madrid Gnrl. You can compare the effects of market volatilities on Russell 2000 and Madrid Gnrl 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 Russell 2000 with a short position of Madrid Gnrl. See also your portfolio center. Please also check ongoing floating volatility patterns of Russell 2000 and Madrid Gnrl.
|Horizon||30 Days Login to change|
Predicted Return Density
Russell 2000 vs. Madrid Gnrl
Given the investment horizon of 30 days, Russell 2000 is expected to under-perform the Madrid Gnrl. In addition to that, Russell 2000 is 1.55 times more volatile than Madrid Gnrl. It trades about -0.17 of its total potential returns per unit of risk. Madrid Gnrl is currently generating about -0.03 per unit of volatility. If you would invest 90,095 in Madrid Gnrl on November 18, 2018 and sell it today you would lose (1,415) from holding Madrid Gnrl or give up 1.57% of portfolio value over 30 days.
Pair Corralation between Russell 2000 and Madrid Gnrl
|Time Period||2 Months [change]|
Diversification Opportunities for Russell 2000 and Madrid Gnrl
Very weak diversification
Overlapping area represents the amount of risk that can be diversified away by holding Russell 2000 and Madrid Gnrl in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on Madrid Gnrl and Russell 2000 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 Russell 2000 are associated (or correlated) with Madrid Gnrl. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Madrid Gnrl has no effect on the direction of Russell 2000 i.e. Russell 2000 and Madrid Gnrl go up and down completely randomly.