Correlation Between CLEAN ENERGY and Clean Energy
Can any of the company-specific risk be diversified away by investing in both CLEAN ENERGY and Clean 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 CLEAN ENERGY and Clean Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between CLEAN ENERGY FUELS and Clean Energy Fuels, you can compare the effects of market volatilities on CLEAN ENERGY and Clean 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 CLEAN ENERGY with a short position of Clean Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of CLEAN ENERGY and Clean Energy.
Diversification Opportunities for CLEAN ENERGY and Clean Energy
0.89 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between CLEAN and Clean is 0.89. Overlapping area represents the amount of risk that can be diversified away by holding CLEAN ENERGY FUELS and Clean Energy Fuels in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Clean Energy Fuels and CLEAN ENERGY 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 ENERGY FUELS are associated (or correlated) with Clean Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Clean Energy Fuels has no effect on the direction of CLEAN ENERGY i.e., CLEAN ENERGY and Clean Energy go up and down completely randomly.
Pair Corralation between CLEAN ENERGY and Clean Energy
Assuming the 90 days trading horizon CLEAN ENERGY FUELS is expected to under-perform the Clean Energy. But the stock apears to be less risky and, when comparing its historical volatility, CLEAN ENERGY FUELS is 1.13 times less risky than Clean Energy. The stock trades about 0.0 of its potential returns per unit of risk. The Clean Energy Fuels is currently generating about 0.0 of returns per unit of risk over similar time horizon. If you would invest 389.00 in Clean Energy Fuels on October 24, 2024 and sell it today you would lose (110.00) from holding Clean Energy Fuels or give up 28.28% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
CLEAN ENERGY FUELS vs. Clean Energy Fuels
Performance |
Timeline |
CLEAN ENERGY FUELS |
Clean Energy Fuels |
CLEAN ENERGY and Clean Energy Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with CLEAN ENERGY and Clean Energy
The main advantage of trading using opposite CLEAN ENERGY and Clean Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if CLEAN ENERGY position performs unexpectedly, Clean 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 Clean Energy will offset losses from the drop in Clean Energy's long position.CLEAN ENERGY vs. Cass Information Systems | CLEAN ENERGY vs. Entravision Communications | CLEAN ENERGY vs. Chengdu PUTIAN Telecommunications | CLEAN ENERGY vs. OFFICE DEPOT |
Clean Energy vs. Beazer Homes USA | Clean Energy vs. CITY OFFICE REIT | Clean Energy vs. PKSHA TECHNOLOGY INC | Clean Energy vs. VELA TECHNOLPLC LS 0001 |
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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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