Correlation Between Commercial Vehicle and GLATFELTER
Can any of the company-specific risk be diversified away by investing in both Commercial Vehicle and GLATFELTER at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Commercial Vehicle and GLATFELTER into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Commercial Vehicle Group and GLATFELTER, you can compare the effects of market volatilities on Commercial Vehicle and GLATFELTER 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 Commercial Vehicle with a short position of GLATFELTER. Check out your portfolio center. Please also check ongoing floating volatility patterns of Commercial Vehicle and GLATFELTER.
Diversification Opportunities for Commercial Vehicle and GLATFELTER
0.59 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Commercial and GLATFELTER is 0.59. Overlapping area represents the amount of risk that can be diversified away by holding Commercial Vehicle Group and GLATFELTER in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on GLATFELTER and Commercial Vehicle 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 Commercial Vehicle Group are associated (or correlated) with GLATFELTER. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of GLATFELTER has no effect on the direction of Commercial Vehicle i.e., Commercial Vehicle and GLATFELTER go up and down completely randomly.
Pair Corralation between Commercial Vehicle and GLATFELTER
Assuming the 90 days trading horizon Commercial Vehicle Group is expected to under-perform the GLATFELTER. In addition to that, Commercial Vehicle is 2.59 times more volatile than GLATFELTER. It trades about -0.02 of its total potential returns per unit of risk. GLATFELTER is currently generating about 0.14 per unit of volatility. If you would invest 1,720 in GLATFELTER on October 20, 2024 and sell it today you would earn a total of 20.00 from holding GLATFELTER or generate 1.16% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 38.89% |
Values | Daily Returns |
Commercial Vehicle Group vs. GLATFELTER
Performance |
Timeline |
Commercial Vehicle |
GLATFELTER |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
Commercial Vehicle and GLATFELTER Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Commercial Vehicle and GLATFELTER
The main advantage of trading using opposite Commercial Vehicle and GLATFELTER positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Commercial Vehicle position performs unexpectedly, GLATFELTER can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in GLATFELTER will offset losses from the drop in GLATFELTER's long position.Commercial Vehicle vs. CALTAGIRONE EDITORE | Commercial Vehicle vs. ADDUS HOMECARE | Commercial Vehicle vs. OFFICE DEPOT | Commercial Vehicle vs. HAVERTY FURNITURE A |
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Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Global Markets Map module to get a quick overview of global market snapshot using zoomable world map. Drill down to check world indexes.
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