Correlation Between Merck and Voxeljet
Can any of the company-specific risk be diversified away by investing in both Merck and Voxeljet 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 Merck and Voxeljet into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Merck Company and Voxeljet Ag, you can compare the effects of market volatilities on Merck and Voxeljet 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 Merck with a short position of Voxeljet. Check out your portfolio center. Please also check ongoing floating volatility patterns of Merck and Voxeljet.
Diversification Opportunities for Merck and Voxeljet
Poor diversification
The 3 months correlation between Merck and Voxeljet is 0.74. Overlapping area represents the amount of risk that can be diversified away by holding Merck Company and Voxeljet Ag in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Voxeljet Ag and Merck 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 Merck Company are associated (or correlated) with Voxeljet. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Voxeljet Ag has no effect on the direction of Merck i.e., Merck and Voxeljet go up and down completely randomly.
Pair Corralation between Merck and Voxeljet
Considering the 90-day investment horizon Merck Company is expected to generate 0.3 times more return on investment than Voxeljet. However, Merck Company is 3.29 times less risky than Voxeljet. It trades about 0.0 of its potential returns per unit of risk. Voxeljet Ag is currently generating about -0.04 per unit of risk. If you would invest 10,333 in Merck Company on September 2, 2024 and sell it today you would lose (169.00) from holding Merck Company or give up 1.64% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 31.05% |
| Values | Daily Returns |
Merck Company vs. Voxeljet Ag
Performance |
| Timeline |
| Merck Company |
| Voxeljet Ag |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
Merck and Voxeljet Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Merck and Voxeljet
The main advantage of trading using opposite Merck and Voxeljet positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Merck position performs unexpectedly, Voxeljet 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 Voxeljet will offset losses from the drop in Voxeljet's long position.The idea behind Merck Company and Voxeljet Ag pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.| Voxeljet vs. Stratasys | Voxeljet vs. Desktop Metal | Voxeljet vs. Nano Dimension | Voxeljet vs. Pure Storage |
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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