Correlation Between Shape Robotics and GreenMobility
Can any of the company-specific risk be diversified away by investing in both Shape Robotics and GreenMobility 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 Shape Robotics and GreenMobility into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Shape Robotics AS and GreenMobility AS, you can compare the effects of market volatilities on Shape Robotics and GreenMobility 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 Shape Robotics with a short position of GreenMobility. Check out your portfolio center. Please also check ongoing floating volatility patterns of Shape Robotics and GreenMobility.
Diversification Opportunities for Shape Robotics and GreenMobility
0.42 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Shape and GreenMobility is 0.42. Overlapping area represents the amount of risk that can be diversified away by holding Shape Robotics AS and GreenMobility AS in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on GreenMobility AS and Shape Robotics 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 Shape Robotics AS are associated (or correlated) with GreenMobility. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of GreenMobility AS has no effect on the direction of Shape Robotics i.e., Shape Robotics and GreenMobility go up and down completely randomly.
Pair Corralation between Shape Robotics and GreenMobility
Assuming the 90 days trading horizon Shape Robotics AS is expected to under-perform the GreenMobility. In addition to that, Shape Robotics is 1.3 times more volatile than GreenMobility AS. It trades about -0.06 of its total potential returns per unit of risk. GreenMobility AS is currently generating about 0.0 per unit of volatility. If you would invest 3,500 in GreenMobility AS on January 24, 2025 and sell it today you would lose (588.00) from holding GreenMobility AS or give up 16.8% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Shape Robotics AS vs. GreenMobility AS
Performance |
| Timeline |
| Shape Robotics AS |
| GreenMobility AS |
Shape Robotics and GreenMobility Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Shape Robotics and GreenMobility
The main advantage of trading using opposite Shape Robotics and GreenMobility positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Shape Robotics position performs unexpectedly, GreenMobility 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 GreenMobility will offset losses from the drop in GreenMobility's long position.| Shape Robotics vs. FOM Technologies AS | Shape Robotics vs. cBrain AS | Shape Robotics vs. Green Hydrogen Systems | Shape Robotics vs. BioPorto |
| GreenMobility vs. BankIn Bredygt Klimaakt | GreenMobility vs. Vestjysk Bank AS | GreenMobility vs. Lollands Bank | GreenMobility vs. Hvidbjerg Bank |
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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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