Correlation Between SIVERS SEMICONDUCTORS and Merck
Can any of the company-specific risk be diversified away by investing in both SIVERS SEMICONDUCTORS and Merck 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 SIVERS SEMICONDUCTORS and Merck into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SIVERS SEMICONDUCTORS AB and Merck Company, you can compare the effects of market volatilities on SIVERS SEMICONDUCTORS and Merck 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 SIVERS SEMICONDUCTORS with a short position of Merck. Check out your portfolio center. Please also check ongoing floating volatility patterns of SIVERS SEMICONDUCTORS and Merck.
Diversification Opportunities for SIVERS SEMICONDUCTORS and Merck
0.86 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between SIVERS and Merck is 0.86. Overlapping area represents the amount of risk that can be diversified away by holding SIVERS SEMICONDUCTORS AB and Merck Company in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Merck Company and SIVERS SEMICONDUCTORS 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 SIVERS SEMICONDUCTORS AB are associated (or correlated) with Merck. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Merck Company has no effect on the direction of SIVERS SEMICONDUCTORS i.e., SIVERS SEMICONDUCTORS and Merck go up and down completely randomly.
Pair Corralation between SIVERS SEMICONDUCTORS and Merck
Assuming the 90 days horizon SIVERS SEMICONDUCTORS AB is expected to under-perform the Merck. In addition to that, SIVERS SEMICONDUCTORS is 3.11 times more volatile than Merck Company. It trades about -0.02 of its total potential returns per unit of risk. Merck Company is currently generating about -0.02 per unit of volatility. If you would invest 17,592 in Merck Company on September 15, 2024 and sell it today you would lose (3,327) from holding Merck Company or give up 18.91% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
SIVERS SEMICONDUCTORS AB vs. Merck Company
Performance |
Timeline |
SIVERS SEMICONDUCTORS |
Merck Company |
SIVERS SEMICONDUCTORS and Merck Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with SIVERS SEMICONDUCTORS and Merck
The main advantage of trading using opposite SIVERS SEMICONDUCTORS and Merck positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SIVERS SEMICONDUCTORS position performs unexpectedly, Merck 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 Merck will offset losses from the drop in Merck's long position.SIVERS SEMICONDUCTORS vs. Playtech plc | SIVERS SEMICONDUCTORS vs. COMBA TELECOM SYST | SIVERS SEMICONDUCTORS vs. Chunghwa Telecom Co | SIVERS SEMICONDUCTORS vs. NetSol Technologies |
Merck vs. Elanco Animal Health | Merck vs. Superior Plus Corp | Merck vs. NMI Holdings | Merck vs. SIVERS SEMICONDUCTORS AB |
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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