Correlation Between Molecular Partners and Golden Energy
Can any of the company-specific risk be diversified away by investing in both Molecular Partners and Golden Energy 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 Molecular Partners and Golden Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Molecular Partners AG and Golden Energy Offshore, you can compare the effects of market volatilities on Molecular Partners and Golden Energy 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 Molecular Partners with a short position of Golden Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Molecular Partners and Golden Energy.
Diversification Opportunities for Molecular Partners and Golden Energy
0.61 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Molecular and Golden is 0.61. Overlapping area represents the amount of risk that can be diversified away by holding Molecular Partners AG and Golden Energy Offshore in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Golden Energy Offshore and Molecular Partners 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 Molecular Partners AG are associated (or correlated) with Golden Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Golden Energy Offshore has no effect on the direction of Molecular Partners i.e., Molecular Partners and Golden Energy go up and down completely randomly.
Pair Corralation between Molecular Partners and Golden Energy
Given the investment horizon of 90 days Molecular Partners AG is expected to generate 6.84 times more return on investment than Golden Energy. However, Molecular Partners is 6.84 times more volatile than Golden Energy Offshore. It trades about 0.04 of its potential returns per unit of risk. Golden Energy Offshore is currently generating about -0.22 per unit of risk. If you would invest 506.00 in Molecular Partners AG on November 7, 2024 and sell it today you would earn a total of 10.00 from holding Molecular Partners AG or generate 1.98% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 90.48% |
| Values | Daily Returns |
Molecular Partners AG vs. Golden Energy Offshore
Performance |
| Timeline |
| Molecular Partners |
| Golden Energy Offshore |
Molecular Partners and Golden Energy Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Molecular Partners and Golden Energy
The main advantage of trading using opposite Molecular Partners and Golden Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Molecular Partners position performs unexpectedly, Golden Energy 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 Golden Energy will offset losses from the drop in Golden Energy's long position.| Molecular Partners vs. Mineralys Therapeutics, Common | Molecular Partners vs. AN2 Therapeutics | Molecular Partners vs. Pharvaris BV | Molecular Partners vs. PepGen |
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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 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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