Correlation Between Materials Select and VanEck Vectors
Can any of the company-specific risk be diversified away by investing in both Materials Select 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 Materials Select and VanEck Vectors into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Materials Select Sector and VanEck Vectors ETF, you can compare the effects of market volatilities on Materials Select 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 Materials Select with a short position of VanEck Vectors. Check out your portfolio center. Please also check ongoing floating volatility patterns of Materials Select and VanEck Vectors.
Diversification Opportunities for Materials Select and VanEck Vectors
0.82 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Materials and VanEck is 0.82. Overlapping area represents the amount of risk that can be diversified away by holding Materials Select Sector and VanEck Vectors ETF in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on VanEck Vectors ETF and Materials Select 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 Materials Select Sector 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 ETF has no effect on the direction of Materials Select i.e., Materials Select and VanEck Vectors go up and down completely randomly.
Pair Corralation between Materials Select and VanEck Vectors
Considering the 90-day investment horizon Materials Select Sector is expected to generate 0.41 times more return on investment than VanEck Vectors. However, Materials Select Sector is 2.47 times less risky than VanEck Vectors. It trades about 0.02 of its potential returns per unit of risk. VanEck Vectors ETF is currently generating about -0.12 per unit of risk. If you would invest 9,474 in Materials Select Sector on August 28, 2024 and sell it today you would earn a total of 32.00 from holding Materials Select Sector or generate 0.34% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 95.45% |
Values | Daily Returns |
Materials Select Sector vs. VanEck Vectors ETF
Performance |
Timeline |
Materials Select Sector |
VanEck Vectors ETF |
Materials Select and VanEck Vectors Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Materials Select and VanEck Vectors
The main advantage of trading using opposite Materials Select and VanEck Vectors positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Materials Select 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.Materials Select vs. Industrial Select Sector | Materials Select vs. Consumer Discretionary Select | Materials Select vs. Consumer Staples Select | Materials Select vs. Utilities Select Sector |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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