Correlation Between Catella AB and EEducation Albert
Can any of the company-specific risk be diversified away by investing in both Catella AB and EEducation Albert 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 Catella AB and EEducation Albert into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Catella AB and eEducation Albert AB, you can compare the effects of market volatilities on Catella AB and EEducation Albert 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 Catella AB with a short position of EEducation Albert. Check out your portfolio center. Please also check ongoing floating volatility patterns of Catella AB and EEducation Albert.
Diversification Opportunities for Catella AB and EEducation Albert
0.63 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Catella and EEducation is 0.63. Overlapping area represents the amount of risk that can be diversified away by holding Catella AB and eEducation Albert AB in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on eEducation Albert and Catella AB 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 Catella AB are associated (or correlated) with EEducation Albert. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of eEducation Albert has no effect on the direction of Catella AB i.e., Catella AB and EEducation Albert go up and down completely randomly.
Pair Corralation between Catella AB and EEducation Albert
Assuming the 90 days trading horizon Catella AB is expected to generate 0.59 times more return on investment than EEducation Albert. However, Catella AB is 1.69 times less risky than EEducation Albert. It trades about -0.03 of its potential returns per unit of risk. eEducation Albert AB is currently generating about -0.07 per unit of risk. If you would invest 3,079 in Catella AB on September 12, 2024 and sell it today you would lose (469.00) from holding Catella AB or give up 15.23% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Catella AB vs. eEducation Albert AB
Performance |
| Timeline |
| Catella AB |
| eEducation Albert |
Catella AB and EEducation Albert Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Catella AB and EEducation Albert
The main advantage of trading using opposite Catella AB and EEducation Albert positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Catella AB position performs unexpectedly, EEducation Albert 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 EEducation Albert will offset losses from the drop in EEducation Albert's long position.| Catella AB vs. Clas Ohlson AB | Catella AB vs. New Wave Group | Catella AB vs. Bilia AB | Catella AB vs. Inwido AB |
| EEducation Albert vs. Greater Than AB | EEducation Albert vs. Cint Group AB | EEducation Albert vs. Acconeer AB | EEducation Albert vs. IAR Systems Group |
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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