Correlation Between Global X and VanEck Vectors
Can any of the company-specific risk be diversified away by investing in both Global X and VanEck Vectors 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 Global X and VanEck Vectors into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Global X 21Shares and VanEck Vectors Australian, you can compare the effects of market volatilities on Global X and VanEck Vectors 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 Global X with a short position of VanEck Vectors. Check out your portfolio center. Please also check ongoing floating volatility patterns of Global X and VanEck Vectors.
Diversification Opportunities for Global X and VanEck Vectors
-0.16 | Correlation Coefficient |
Good diversification
The 3 months correlation between Global and VanEck is -0.16. Overlapping area represents the amount of risk that can be diversified away by holding Global X 21Shares and VanEck Vectors Australian in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on VanEck Vectors Australian and Global X 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 Global X 21Shares are associated (or correlated) with VanEck Vectors. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of VanEck Vectors Australian has no effect on the direction of Global X i.e., Global X and VanEck Vectors go up and down completely randomly.
Pair Corralation between Global X and VanEck Vectors
Assuming the 90 days trading horizon Global X 21Shares is expected to generate 3.53 times more return on investment than VanEck Vectors. However, Global X is 3.53 times more volatile than VanEck Vectors Australian. It trades about 0.1 of its potential returns per unit of risk. VanEck Vectors Australian is currently generating about 0.27 per unit of risk. If you would invest 1,561 in Global X 21Shares on November 5, 2024 and sell it today you would earn a total of 58.00 from holding Global X 21Shares or generate 3.72% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Global X 21Shares vs. VanEck Vectors Australian
Performance |
| Timeline |
| Global X 21Shares |
| VanEck Vectors Australian |
Global X and VanEck Vectors Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Global X and VanEck Vectors
The main advantage of trading using opposite Global X and VanEck Vectors positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Global X position performs unexpectedly, VanEck Vectors 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 VanEck Vectors will offset losses from the drop in VanEck Vectors' long position.| Global X vs. Global X Hydrogen | Global X vs. Global X Physical | Global X vs. Global X Treasury | Global X vs. Global X Physical |
| VanEck Vectors vs. VanEck FTSE China | VanEck Vectors vs. VanEck MSCI International | VanEck Vectors vs. VanEck Global Clean | VanEck Vectors vs. VanEck MSCI Australian |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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