This module allows you to analyze existing cross correlation between BSE and NASDAQ Italy. You can compare the effects of market volatilities on BSE and NASDAQ Italy 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 BSE with a short position of NASDAQ Italy. See also your portfolio center. Please also check ongoing floating volatility patterns of BSE and NASDAQ Italy.
|Horizon||30 Days Login to change|
Predicted Return Density
BSE vs. NASDAQ Italy
Assuming 30 trading days horizon, BSE is expected to generate 1.05 times more return on investment than NASDAQ Italy. However, BSE is 1.05 times more volatile than NASDAQ Italy. It trades about 0.03 of its potential returns per unit of risk. NASDAQ Italy is currently generating about -0.2 per unit of risk. If you would invest 3,914,028 in BSE on May 17, 2019 and sell it today you would earn a total of 31,179 from holding BSE or generate 0.8% return on investment over 30 days.
Pair Corralation between BSE and NASDAQ Italy
|Time Period||2 Months [change]|
Diversification Opportunities for BSE and NASDAQ Italy
Very good diversification
Overlapping area represents the amount of risk that can be diversified away by holding BSE and NASDAQ Italy in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on NASDAQ Italy and BSE 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 BSE are associated (or correlated) with NASDAQ Italy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of NASDAQ Italy has no effect on the direction of BSE i.e. BSE and NASDAQ Italy 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.