This module allows you to analyze existing cross correlation between NZSE and SPTSX Comp. You can compare the effects of market volatilities on NZSE and SPTSX Comp 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 NZSE with a short position of SPTSX Comp. See also your portfolio center. Please also check ongoing floating volatility patterns of NZSE and SPTSX Comp.
|Horizon||30 Days Login to change|
Predicted Return Density
NZSE vs. SPTSX Comp
Assuming 30 trading days horizon, NZSE is expected to generate 1.15 times more return on investment than SPTSX Comp. However, NZSE is 1.15 times more volatile than SPTSX Comp. It trades about 0.07 of its potential returns per unit of risk. SPTSX Comp is currently generating about 0.01 per unit of risk. If you would invest 1,065,480 in NZSE on September 15, 2019 and sell it today you would earn a total of 37,180 from holding NZSE or generate 3.49% return on investment over 30 days.
Pair Corralation between NZSE and SPTSX Comp
|Time Period||3 Months [change]|
Diversification Opportunities for NZSE and SPTSX Comp
Overlapping area represents the amount of risk that can be diversified away by holding NZSE and SPTSX Comp in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on SPTSX Comp and NZSE 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 NZSE are associated (or correlated) with SPTSX Comp. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SPTSX Comp has no effect on the direction of NZSE i.e. NZSE and SPTSX Comp 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.