Correlation Between STMICROELECTRONICS and Zimmer Biomet
Can any of the company-specific risk be diversified away by investing in both STMICROELECTRONICS and Zimmer Biomet 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 STMICROELECTRONICS and Zimmer Biomet into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between STMICROELECTRONICS and Zimmer Biomet Holdings, you can compare the effects of market volatilities on STMICROELECTRONICS and Zimmer Biomet 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 STMICROELECTRONICS with a short position of Zimmer Biomet. Check out your portfolio center. Please also check ongoing floating volatility patterns of STMICROELECTRONICS and Zimmer Biomet.
Diversification Opportunities for STMICROELECTRONICS and Zimmer Biomet
-0.66 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between STMICROELECTRONICS and Zimmer is -0.66. Overlapping area represents the amount of risk that can be diversified away by holding STMICROELECTRONICS and Zimmer Biomet Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Zimmer Biomet Holdings and STMICROELECTRONICS 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 STMICROELECTRONICS are associated (or correlated) with Zimmer Biomet. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Zimmer Biomet Holdings has no effect on the direction of STMICROELECTRONICS i.e., STMICROELECTRONICS and Zimmer Biomet go up and down completely randomly.
Pair Corralation between STMICROELECTRONICS and Zimmer Biomet
Assuming the 90 days trading horizon STMICROELECTRONICS is expected to under-perform the Zimmer Biomet. In addition to that, STMICROELECTRONICS is 1.64 times more volatile than Zimmer Biomet Holdings. It trades about -0.06 of its total potential returns per unit of risk. Zimmer Biomet Holdings is currently generating about -0.01 per unit of volatility. If you would invest 11,087 in Zimmer Biomet Holdings on October 4, 2024 and sell it today you would lose (917.00) from holding Zimmer Biomet Holdings or give up 8.27% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 99.7% |
Values | Daily Returns |
STMICROELECTRONICS vs. Zimmer Biomet Holdings
Performance |
Timeline |
STMICROELECTRONICS |
Zimmer Biomet Holdings |
STMICROELECTRONICS and Zimmer Biomet Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with STMICROELECTRONICS and Zimmer Biomet
The main advantage of trading using opposite STMICROELECTRONICS and Zimmer Biomet positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if STMICROELECTRONICS position performs unexpectedly, Zimmer Biomet 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 Zimmer Biomet will offset losses from the drop in Zimmer Biomet's long position.STMICROELECTRONICS vs. YATRA ONLINE DL 0001 | STMICROELECTRONICS vs. Safety Insurance Group | STMICROELECTRONICS vs. Selective Insurance Group | STMICROELECTRONICS vs. Zurich Insurance Group |
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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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