This module allows you to analyze existing cross correlation between NQTH and EURONEXT BEL-20. You can compare the effects of market volatilities on NQTH and EURONEXT BEL-20 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 NQTH with a short position of EURONEXT BEL-20. See also your portfolio center. Please also check ongoing floating volatility patterns of NQTH and EURONEXT BEL-20.
|Horizon||30 Days Login to change|
Predicted Return Density
NQTH vs. EURONEXT BEL-20
Assuming 30 trading days horizon, NQTH is expected to generate 0.64 times more return on investment than EURONEXT BEL-20. However, NQTH is 1.57 times less risky than EURONEXT BEL-20. It trades about 0.05 of its potential returns per unit of risk. EURONEXT BEL-20 is currently generating about -0.23 per unit of risk. If you would invest 115,285 in NQTH on May 19, 2019 and sell it today you would earn a total of 1,407 from holding NQTH or generate 1.22% return on investment over 30 days.
Pair Corralation between NQTH and EURONEXT BEL-20
|Time Period||2 Months [change]|
Diversification Opportunities for NQTH and EURONEXT BEL-20
Overlapping area represents the amount of risk that can be diversified away by holding NQTH and EURONEXT BEL-20 in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on EURONEXT BEL-20 and NQTH 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 NQTH are associated (or correlated) with EURONEXT BEL-20. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of EURONEXT BEL-20 has no effect on the direction of NQTH i.e. NQTH and EURONEXT BEL-20 go up and down completely randomly.
See also your portfolio center. Please also try Price Transformation module to use price transformation models to analyze depth of different equity instruments across global markets.