Correlation Between Agroliga Group and Clean Carbon
Can any of the company-specific risk be diversified away by investing in both Agroliga Group and Clean Carbon 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 Agroliga Group and Clean Carbon into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Agroliga Group PLC and Clean Carbon Energy, you can compare the effects of market volatilities on Agroliga Group and Clean Carbon 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 Agroliga Group with a short position of Clean Carbon. Check out your portfolio center. Please also check ongoing floating volatility patterns of Agroliga Group and Clean Carbon.
Diversification Opportunities for Agroliga Group and Clean Carbon
-0.39 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Agroliga and Clean is -0.39. Overlapping area represents the amount of risk that can be diversified away by holding Agroliga Group PLC and Clean Carbon Energy in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Clean Carbon Energy and Agroliga Group 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 Agroliga Group PLC are associated (or correlated) with Clean Carbon. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Clean Carbon Energy has no effect on the direction of Agroliga Group i.e., Agroliga Group and Clean Carbon go up and down completely randomly.
Pair Corralation between Agroliga Group and Clean Carbon
Assuming the 90 days trading horizon Agroliga Group is expected to generate 3.16 times less return on investment than Clean Carbon. But when comparing it to its historical volatility, Agroliga Group PLC is 3.14 times less risky than Clean Carbon. It trades about 0.11 of its potential returns per unit of risk. Clean Carbon Energy is currently generating about 0.11 of returns per unit of risk over similar time horizon. If you would invest 28.00 in Clean Carbon Energy on August 27, 2024 and sell it today you would earn a total of 3.00 from holding Clean Carbon Energy or generate 10.71% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 89.47% |
| Values | Daily Returns |
Agroliga Group PLC vs. Clean Carbon Energy
Performance |
| Timeline |
| Agroliga Group PLC |
| Clean Carbon Energy |
Agroliga Group and Clean Carbon Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Agroliga Group and Clean Carbon
The main advantage of trading using opposite Agroliga Group and Clean Carbon positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Agroliga Group position performs unexpectedly, Clean Carbon 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 Clean Carbon will offset losses from the drop in Clean Carbon's long position.| Agroliga Group vs. Clean Carbon Energy | Agroliga Group vs. ADX | Agroliga Group vs. Vee SA | Agroliga Group vs. Novina SA |
| Clean Carbon vs. Asseco Business Solutions | Clean Carbon vs. Detalion Games SA | Clean Carbon vs. Asseco South Eastern | Clean Carbon vs. CFI Holding SA |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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