Correlation Between NISSAN CHEMICAL and Clean Energy
Can any of the company-specific risk be diversified away by investing in both NISSAN CHEMICAL 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 NISSAN CHEMICAL and Clean Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NISSAN CHEMICAL IND and Clean Energy Fuels, you can compare the effects of market volatilities on NISSAN CHEMICAL 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 NISSAN CHEMICAL with a short position of Clean Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of NISSAN CHEMICAL and Clean Energy.
Diversification Opportunities for NISSAN CHEMICAL and Clean Energy
0.07 | Correlation Coefficient |
Significant diversification
The 3 months correlation between NISSAN and Clean is 0.07. Overlapping area represents the amount of risk that can be diversified away by holding NISSAN CHEMICAL IND 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 NISSAN CHEMICAL 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 NISSAN CHEMICAL IND 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 NISSAN CHEMICAL i.e., NISSAN CHEMICAL and Clean Energy go up and down completely randomly.
Pair Corralation between NISSAN CHEMICAL and Clean Energy
Assuming the 90 days trading horizon NISSAN CHEMICAL IND is expected to generate 0.44 times more return on investment than Clean Energy. However, NISSAN CHEMICAL IND is 2.28 times less risky than Clean Energy. It trades about -0.03 of its potential returns per unit of risk. Clean Energy Fuels is currently generating about -0.01 per unit of risk. If you would invest 4,240 in NISSAN CHEMICAL IND on September 12, 2024 and sell it today you would lose (1,100) from holding NISSAN CHEMICAL IND or give up 25.94% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
NISSAN CHEMICAL IND vs. Clean Energy Fuels
Performance |
Timeline |
NISSAN CHEMICAL IND |
Clean Energy Fuels |
NISSAN CHEMICAL and Clean Energy Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with NISSAN CHEMICAL and Clean Energy
The main advantage of trading using opposite NISSAN CHEMICAL and Clean Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NISSAN CHEMICAL 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.NISSAN CHEMICAL vs. Apple Inc | NISSAN CHEMICAL vs. Apple Inc | NISSAN CHEMICAL vs. Apple Inc | NISSAN CHEMICAL vs. Apple Inc |
Clean Energy vs. NISSAN CHEMICAL IND | Clean Energy vs. PRECISION DRILLING P | Clean Energy vs. Consolidated Communications Holdings | Clean Energy vs. Nissan Chemical Corp |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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