Correlation Between APPLIED MATERIALS and CanSino Biologics
Can any of the company-specific risk be diversified away by investing in both APPLIED MATERIALS and CanSino Biologics 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 APPLIED MATERIALS and CanSino Biologics into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between APPLIED MATERIALS and CanSino Biologics, you can compare the effects of market volatilities on APPLIED MATERIALS and CanSino Biologics 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 APPLIED MATERIALS with a short position of CanSino Biologics. Check out your portfolio center. Please also check ongoing floating volatility patterns of APPLIED MATERIALS and CanSino Biologics.
Diversification Opportunities for APPLIED MATERIALS and CanSino Biologics
-0.28 | Correlation Coefficient |
Very good diversification
The 3 months correlation between APPLIED and CanSino is -0.28. Overlapping area represents the amount of risk that can be diversified away by holding APPLIED MATERIALS and CanSino Biologics in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CanSino Biologics and APPLIED MATERIALS 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 APPLIED MATERIALS are associated (or correlated) with CanSino Biologics. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CanSino Biologics has no effect on the direction of APPLIED MATERIALS i.e., APPLIED MATERIALS and CanSino Biologics go up and down completely randomly.
Pair Corralation between APPLIED MATERIALS and CanSino Biologics
Assuming the 90 days trading horizon APPLIED MATERIALS is expected to generate 1.4 times more return on investment than CanSino Biologics. However, APPLIED MATERIALS is 1.4 times more volatile than CanSino Biologics. It trades about 0.06 of its potential returns per unit of risk. CanSino Biologics is currently generating about 0.03 per unit of risk. If you would invest 17,026 in APPLIED MATERIALS on November 8, 2024 and sell it today you would earn a total of 518.00 from holding APPLIED MATERIALS or generate 3.04% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 95.65% |
Values | Daily Returns |
APPLIED MATERIALS vs. CanSino Biologics
Performance |
Timeline |
APPLIED MATERIALS |
CanSino Biologics |
APPLIED MATERIALS and CanSino Biologics Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with APPLIED MATERIALS and CanSino Biologics
The main advantage of trading using opposite APPLIED MATERIALS and CanSino Biologics positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if APPLIED MATERIALS position performs unexpectedly, CanSino Biologics 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 CanSino Biologics will offset losses from the drop in CanSino Biologics' long position.APPLIED MATERIALS vs. VULCAN MATERIALS | APPLIED MATERIALS vs. Rayonier Advanced Materials | APPLIED MATERIALS vs. ITALIAN WINE BRANDS | APPLIED MATERIALS vs. Mitsubishi Materials |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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