Correlation Between Powercell Sweden and CureVac NV
Can any of the company-specific risk be diversified away by investing in both Powercell Sweden and CureVac NV 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 Powercell Sweden and CureVac NV into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Powercell Sweden and CureVac NV, you can compare the effects of market volatilities on Powercell Sweden and CureVac NV 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 Powercell Sweden with a short position of CureVac NV. Check out your portfolio center. Please also check ongoing floating volatility patterns of Powercell Sweden and CureVac NV.
Diversification Opportunities for Powercell Sweden and CureVac NV
-0.54 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Powercell and CureVac is -0.54. Overlapping area represents the amount of risk that can be diversified away by holding Powercell Sweden and CureVac NV in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CureVac NV and Powercell Sweden 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 Powercell Sweden are associated (or correlated) with CureVac NV. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CureVac NV has no effect on the direction of Powercell Sweden i.e., Powercell Sweden and CureVac NV go up and down completely randomly.
Pair Corralation between Powercell Sweden and CureVac NV
Assuming the 90 days horizon Powercell Sweden is expected to generate 2.15 times more return on investment than CureVac NV. However, Powercell Sweden is 2.15 times more volatile than CureVac NV. It trades about 0.04 of its potential returns per unit of risk. CureVac NV is currently generating about -0.07 per unit of risk. If you would invest 277.00 in Powercell Sweden on August 25, 2024 and sell it today you would earn a total of 5.00 from holding Powercell Sweden or generate 1.81% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Powercell Sweden vs. CureVac NV
Performance |
| Timeline |
| Powercell Sweden |
| CureVac NV |
Powercell Sweden and CureVac NV Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Powercell Sweden and CureVac NV
The main advantage of trading using opposite Powercell Sweden and CureVac NV positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Powercell Sweden position performs unexpectedly, CureVac NV 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 CureVac NV will offset losses from the drop in CureVac NV's long position.| Powercell Sweden vs. YASKAWA ELEC UNSP | Powercell Sweden vs. Varta AG | Powercell Sweden vs. OSRAM LICHT N | Powercell Sweden vs. Bloom Energy |
| CureVac NV vs. CSL Limited | CureVac NV vs. Superior Plus Corp | CureVac NV vs. NMI Holdings | CureVac NV vs. Origin Agritech |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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