Correlation Between Zealand Pharma and Bavarian Nordic
Can any of the company-specific risk be diversified away by investing in both Zealand Pharma and Bavarian Nordic 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 Zealand Pharma and Bavarian Nordic into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Zealand Pharma AS and Bavarian Nordic, you can compare the effects of market volatilities on Zealand Pharma and Bavarian Nordic 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 Zealand Pharma with a short position of Bavarian Nordic. Check out your portfolio center. Please also check ongoing floating volatility patterns of Zealand Pharma and Bavarian Nordic.
Diversification Opportunities for Zealand Pharma and Bavarian Nordic
0.79 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Zealand and Bavarian is 0.79. Overlapping area represents the amount of risk that can be diversified away by holding Zealand Pharma AS and Bavarian Nordic in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bavarian Nordic and Zealand Pharma 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 Zealand Pharma AS are associated (or correlated) with Bavarian Nordic. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bavarian Nordic has no effect on the direction of Zealand Pharma i.e., Zealand Pharma and Bavarian Nordic go up and down completely randomly.
Pair Corralation between Zealand Pharma and Bavarian Nordic
Assuming the 90 days trading horizon Zealand Pharma AS is expected to generate 0.88 times more return on investment than Bavarian Nordic. However, Zealand Pharma AS is 1.13 times less risky than Bavarian Nordic. It trades about -0.08 of its potential returns per unit of risk. Bavarian Nordic is currently generating about -0.13 per unit of risk. If you would invest 87,000 in Zealand Pharma AS on September 2, 2024 and sell it today you would lose (14,000) from holding Zealand Pharma AS or give up 16.09% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Zealand Pharma AS vs. Bavarian Nordic
Performance |
Timeline |
Zealand Pharma AS |
Bavarian Nordic |
Zealand Pharma and Bavarian Nordic Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Zealand Pharma and Bavarian Nordic
The main advantage of trading using opposite Zealand Pharma and Bavarian Nordic positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Zealand Pharma position performs unexpectedly, Bavarian Nordic 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 Bavarian Nordic will offset losses from the drop in Bavarian Nordic's long position.Zealand Pharma vs. Bavarian Nordic | Zealand Pharma vs. Ambu AS | Zealand Pharma vs. Genmab AS | Zealand Pharma vs. ALK Abell AS |
Bavarian Nordic vs. Ambu AS | Bavarian Nordic vs. Danske Bank AS | Bavarian Nordic vs. Genmab AS | Bavarian Nordic vs. DSV Panalpina AS |
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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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