Correlation Between Palfinger and Zumtobel Group
Can any of the company-specific risk be diversified away by investing in both Palfinger and Zumtobel Group 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 Palfinger and Zumtobel Group into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Palfinger AG and Zumtobel Group AG, you can compare the effects of market volatilities on Palfinger and Zumtobel Group 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 Palfinger with a short position of Zumtobel Group. Check out your portfolio center. Please also check ongoing floating volatility patterns of Palfinger and Zumtobel Group.
Diversification Opportunities for Palfinger and Zumtobel Group
0.83 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Palfinger and Zumtobel is 0.83. Overlapping area represents the amount of risk that can be diversified away by holding Palfinger AG and Zumtobel Group AG in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Zumtobel Group AG and Palfinger 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 Palfinger AG are associated (or correlated) with Zumtobel Group. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Zumtobel Group AG has no effect on the direction of Palfinger i.e., Palfinger and Zumtobel Group go up and down completely randomly.
Pair Corralation between Palfinger and Zumtobel Group
Assuming the 90 days trading horizon Palfinger AG is expected to generate 0.83 times more return on investment than Zumtobel Group. However, Palfinger AG is 1.2 times less risky than Zumtobel Group. It trades about -0.05 of its potential returns per unit of risk. Zumtobel Group AG is currently generating about -0.04 per unit of risk. If you would invest 2,345 in Palfinger AG on September 2, 2024 and sell it today you would lose (405.00) from holding Palfinger AG or give up 17.27% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Palfinger AG vs. Zumtobel Group AG
Performance |
| Timeline |
| Palfinger AG |
| Zumtobel Group AG |
Palfinger and Zumtobel Group Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Palfinger and Zumtobel Group
The main advantage of trading using opposite Palfinger and Zumtobel Group positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Palfinger position performs unexpectedly, Zumtobel Group 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 Zumtobel Group will offset losses from the drop in Zumtobel Group's long position.| Palfinger vs. RATH Aktiengesellschaft | Palfinger vs. Semperit Aktiengesellschaft Holding | Palfinger vs. Telekom Austria AG | Palfinger vs. Oesterr Post AG |
| Zumtobel Group vs. Voestalpine AG | Zumtobel Group vs. Andritz AG | Zumtobel Group vs. Wienerberger AG | Zumtobel Group vs. Lenzing Aktiengesellschaft |
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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