This module allows you to analyze existing cross correlation between Stockholm and IBEX 35. You can compare the effects of market volatilities on Stockholm and IBEX 35 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 Stockholm with a short position of IBEX 35. See also your portfolio center. Please also check ongoing floating volatility patterns of Stockholm and IBEX 35.
|Horizon||30 Days Login to change|
Predicted Return Density
Stockholm vs. IBEX 35
Assuming 30 trading days horizon, Stockholm is expected to generate 1.23 times more return on investment than IBEX 35. However, Stockholm is 1.23 times more volatile than IBEX 35. It trades about -0.08 of its potential returns per unit of risk. IBEX 35 is currently generating about -0.16 per unit of risk. If you would invest 61,971 in Stockholm on May 19, 2019 and sell it today you would lose (1,696) from holding Stockholm or give up 2.74% of portfolio value over 30 days.
Pair Corralation between Stockholm and IBEX 35
|Time Period||2 Months [change]|
Diversification Opportunities for Stockholm and IBEX 35
Overlapping area represents the amount of risk that can be diversified away by holding Stockholm and IBEX 35 in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on IBEX 35 and Stockholm 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 Stockholm are associated (or correlated) with IBEX 35. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of IBEX 35 has no effect on the direction of Stockholm i.e. Stockholm and IBEX 35 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.