- Companies in United States
- Peer Analysis
This module allows you to analyze existing cross correlation between General Motors Company and NASDAQ UK. You can compare the effects of market volatilities on GM and NASDAQ UK 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 GM with a short position of NASDAQ UK. See also your portfolio center. Please also check ongoing floating volatility patterns of GM and NASDAQ UK.
|Horizon||30 Days Login to change|
Predicted Return Density
General Motors Company vs. NASDAQ UK
Allowing for the 30-days total investment horizon, General Motors Company is expected to under-perform the NASDAQ UK. In addition to that, GM is 1.55 times more volatile than NASDAQ UK. It trades about -0.03 of its total potential returns per unit of risk. NASDAQ UK is currently generating about 0.25 per unit of volatility. If you would invest 97,919 in NASDAQ UK on February 17, 2019 and sell it today you would earn a total of 7,077 from holding NASDAQ UK or generate 7.23% return on investment over 30 days.
Pair Corralation between GM and NASDAQ UK
|Time Period||2 Months [change]|
Diversification Opportunities for GM and NASDAQ UK
Very weak diversification
Overlapping area represents the amount of risk that can be diversified away by holding General Motors Company and NASDAQ UK in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on NASDAQ UK and GM 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 General Motors Company are associated (or correlated) with NASDAQ UK. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of NASDAQ UK has no effect on the direction of GM i.e. GM and NASDAQ UK go up and down completely randomly.