Correlation Between Aluflexpack and SoftwareONE Holding
Can any of the company-specific risk be diversified away by investing in both Aluflexpack and SoftwareONE Holding 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 Aluflexpack and SoftwareONE Holding into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Aluflexpack AG and SoftwareONE Holding AG, you can compare the effects of market volatilities on Aluflexpack and SoftwareONE Holding 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 Aluflexpack with a short position of SoftwareONE Holding. Check out your portfolio center. Please also check ongoing floating volatility patterns of Aluflexpack and SoftwareONE Holding.
Diversification Opportunities for Aluflexpack and SoftwareONE Holding
0.44 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Aluflexpack and SoftwareONE is 0.44. Overlapping area represents the amount of risk that can be diversified away by holding Aluflexpack AG and SoftwareONE Holding AG in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SoftwareONE Holding and Aluflexpack 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 Aluflexpack AG are associated (or correlated) with SoftwareONE Holding. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SoftwareONE Holding has no effect on the direction of Aluflexpack i.e., Aluflexpack and SoftwareONE Holding go up and down completely randomly.
Pair Corralation between Aluflexpack and SoftwareONE Holding
Assuming the 90 days trading horizon Aluflexpack is expected to generate 20.39 times less return on investment than SoftwareONE Holding. But when comparing it to its historical volatility, Aluflexpack AG is 11.75 times less risky than SoftwareONE Holding. It trades about 0.1 of its potential returns per unit of risk. SoftwareONE Holding AG is currently generating about 0.17 of returns per unit of risk over similar time horizon. If you would invest 516.00 in SoftwareONE Holding AG on April 23, 2025 and sell it today you would earn a total of 177.00 from holding SoftwareONE Holding AG or generate 34.3% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Aluflexpack AG vs. SoftwareONE Holding AG
Performance |
Timeline |
Aluflexpack AG |
SoftwareONE Holding |
Aluflexpack and SoftwareONE Holding Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Aluflexpack and SoftwareONE Holding
The main advantage of trading using opposite Aluflexpack and SoftwareONE Holding positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Aluflexpack position performs unexpectedly, SoftwareONE Holding 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 SoftwareONE Holding will offset losses from the drop in SoftwareONE Holding's long position.Aluflexpack vs. VAT Group AG | Aluflexpack vs. Barry Callebaut AG | Aluflexpack vs. SGS SA | Aluflexpack vs. Galenica Sante AG |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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