Correlation Between Carnegie Clean and Brenmiller Energy
Can any of the company-specific risk be diversified away by investing in both Carnegie Clean and Brenmiller Energy 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 Carnegie Clean and Brenmiller Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Carnegie Clean Energy and Brenmiller Energy Ltd, you can compare the effects of market volatilities on Carnegie Clean and Brenmiller Energy 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 Carnegie Clean with a short position of Brenmiller Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Carnegie Clean and Brenmiller Energy.
Diversification Opportunities for Carnegie Clean and Brenmiller Energy
-0.13 | Correlation Coefficient |
Good diversification
The 3 months correlation between Carnegie and Brenmiller is -0.13. Overlapping area represents the amount of risk that can be diversified away by holding Carnegie Clean Energy and Brenmiller Energy Ltd in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Brenmiller Energy and Carnegie Clean 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 Carnegie Clean Energy are associated (or correlated) with Brenmiller Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Brenmiller Energy has no effect on the direction of Carnegie Clean i.e., Carnegie Clean and Brenmiller Energy go up and down completely randomly.
Pair Corralation between Carnegie Clean and Brenmiller Energy
Assuming the 90 days horizon Carnegie Clean Energy is expected to generate 2.01 times more return on investment than Brenmiller Energy. However, Carnegie Clean is 2.01 times more volatile than Brenmiller Energy Ltd. It trades about 0.11 of its potential returns per unit of risk. Brenmiller Energy Ltd is currently generating about 0.05 per unit of risk. If you would invest 2.10 in Carnegie Clean Energy on December 31, 2024 and sell it today you would earn a total of 0.45 from holding Carnegie Clean Energy or generate 21.43% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 98.39% |
Values | Daily Returns |
Carnegie Clean Energy vs. Brenmiller Energy Ltd
Performance |
Timeline |
Carnegie Clean Energy |
Brenmiller Energy |
Carnegie Clean and Brenmiller Energy Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Carnegie Clean and Brenmiller Energy
The main advantage of trading using opposite Carnegie Clean and Brenmiller Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Carnegie Clean position performs unexpectedly, Brenmiller Energy 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 Brenmiller Energy will offset losses from the drop in Brenmiller Energy's long position.Carnegie Clean vs. Astra Energy | Carnegie Clean vs. Brenmiller Energy Ltd | Carnegie Clean vs. Clean Vision Corp | Carnegie Clean vs. Alternus Energy Group |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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