Correlation Between Examobile and Clean Carbon
Can any of the company-specific risk be diversified away by investing in both Examobile 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 Examobile and Clean Carbon into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Examobile SA and Clean Carbon Energy, you can compare the effects of market volatilities on Examobile 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 Examobile with a short position of Clean Carbon. Check out your portfolio center. Please also check ongoing floating volatility patterns of Examobile and Clean Carbon.
Diversification Opportunities for Examobile and Clean Carbon
-0.35 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Examobile and Clean is -0.35. Overlapping area represents the amount of risk that can be diversified away by holding Examobile SA 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 Examobile 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 Examobile SA 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 Examobile i.e., Examobile and Clean Carbon go up and down completely randomly.
Pair Corralation between Examobile and Clean Carbon
Assuming the 90 days trading horizon Examobile SA is expected to under-perform the Clean Carbon. But the stock apears to be less risky and, when comparing its historical volatility, Examobile SA is 1.8 times less risky than Clean Carbon. The stock trades about -0.05 of its potential returns per unit of risk. The Clean Carbon Energy is currently generating about 0.02 of returns per unit of risk over similar time horizon. If you would invest 44.00 in Clean Carbon Energy on November 5, 2024 and sell it today you would lose (4.00) from holding Clean Carbon Energy or give up 9.09% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 69.59% |
| Values | Daily Returns |
Examobile SA vs. Clean Carbon Energy
Performance |
| Timeline |
| Examobile SA |
| Clean Carbon Energy |
Examobile and Clean Carbon Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Examobile and Clean Carbon
The main advantage of trading using opposite Examobile and Clean Carbon positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Examobile 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.| Examobile vs. Movie Games SA | Examobile vs. M Food SA | Examobile vs. Varsav Game Studios | Examobile vs. Alior Bank SA |
| Clean Carbon vs. Drago entertainment SA | Clean Carbon vs. Mercator Medical SA | Clean Carbon vs. Quantum Software SA | Clean Carbon vs. Immobile |
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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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