Correlation Between METALL ZUG and Applied Materials
Can any of the company-specific risk be diversified away by investing in both METALL ZUG and Applied Materials 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 METALL ZUG and Applied Materials into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between METALL ZUG AG and Applied Materials, you can compare the effects of market volatilities on METALL ZUG and Applied Materials 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 METALL ZUG with a short position of Applied Materials. Check out your portfolio center. Please also check ongoing floating volatility patterns of METALL ZUG and Applied Materials.
Diversification Opportunities for METALL ZUG and Applied Materials
0.71 | Correlation Coefficient |
Poor diversification
The 3 months correlation between METALL and Applied is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding METALL ZUG AG and Applied Materials in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Applied Materials and METALL ZUG 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 METALL ZUG AG are associated (or correlated) with Applied Materials. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Applied Materials has no effect on the direction of METALL ZUG i.e., METALL ZUG and Applied Materials go up and down completely randomly.
Pair Corralation between METALL ZUG and Applied Materials
Assuming the 90 days trading horizon METALL ZUG AG is expected to generate 0.68 times more return on investment than Applied Materials. However, METALL ZUG AG is 1.46 times less risky than Applied Materials. It trades about -0.09 of its potential returns per unit of risk. Applied Materials is currently generating about -0.18 per unit of risk. If you would invest 117,000 in METALL ZUG AG on September 23, 2024 and sell it today you would lose (2,500) from holding METALL ZUG AG or give up 2.14% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 72.73% |
Values | Daily Returns |
METALL ZUG AG vs. Applied Materials
Performance |
Timeline |
METALL ZUG AG |
Applied Materials |
METALL ZUG and Applied Materials Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with METALL ZUG and Applied Materials
The main advantage of trading using opposite METALL ZUG and Applied Materials positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if METALL ZUG position performs unexpectedly, Applied Materials 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 Applied Materials will offset losses from the drop in Applied Materials' long position.METALL ZUG vs. Schroders Investment Trusts | METALL ZUG vs. MoneysupermarketCom Group PLC | METALL ZUG vs. Solstad Offshore ASA | METALL ZUG vs. National Beverage Corp |
Applied Materials vs. GreenX Metals | Applied Materials vs. METALL ZUG AG | Applied Materials vs. Amedeo Air Four | Applied Materials vs. Endeavour Mining Corp |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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