Correlation Between Clean Carbon and CFI Holding
Can any of the company-specific risk be diversified away by investing in both Clean Carbon and CFI 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 Clean Carbon and CFI Holding into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Clean Carbon Energy and CFI Holding SA, you can compare the effects of market volatilities on Clean Carbon and CFI 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 Clean Carbon with a short position of CFI Holding. Check out your portfolio center. Please also check ongoing floating volatility patterns of Clean Carbon and CFI Holding.
Diversification Opportunities for Clean Carbon and CFI Holding
0.56 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Clean and CFI is 0.56. Overlapping area represents the amount of risk that can be diversified away by holding Clean Carbon Energy and CFI Holding SA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CFI Holding SA and Clean Carbon 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 Clean Carbon Energy are associated (or correlated) with CFI Holding. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CFI Holding SA has no effect on the direction of Clean Carbon i.e., Clean Carbon and CFI Holding go up and down completely randomly.
Pair Corralation between Clean Carbon and CFI Holding
Assuming the 90 days trading horizon Clean Carbon Energy is expected to under-perform the CFI Holding. But the stock apears to be less risky and, when comparing its historical volatility, Clean Carbon Energy is 1.06 times less risky than CFI Holding. The stock trades about -0.1 of its potential returns per unit of risk. The CFI Holding SA is currently generating about -0.04 of returns per unit of risk over similar time horizon. If you would invest 20.00 in CFI Holding SA on September 5, 2024 and sell it today you would lose (2.00) from holding CFI Holding SA or give up 10.0% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Clean Carbon Energy vs. CFI Holding SA
Performance |
| Timeline |
| Clean Carbon Energy |
| CFI Holding SA |
Clean Carbon and CFI Holding Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Clean Carbon and CFI Holding
The main advantage of trading using opposite Clean Carbon and CFI Holding positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Clean Carbon position performs unexpectedly, CFI 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 CFI Holding will offset losses from the drop in CFI Holding's long position.| Clean Carbon vs. New Tech Venture | Clean Carbon vs. PZ Cormay SA | Clean Carbon vs. Biztech Konsulting SA | Clean Carbon vs. Road Studio SA |
| CFI Holding vs. Globe Trade Centre | CFI Holding vs. Carlson Investments SA | CFI Holding vs. SOFTWARE MANSION SPOLKA | CFI Holding vs. Logintrade 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 Competition Analyzer module to analyze and compare many basic indicators for a group of related or unrelated entities.
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