Correlation Between GEELY AUTOMOBILE and Carnegie Clean
Can any of the company-specific risk be diversified away by investing in both GEELY AUTOMOBILE and Carnegie Clean 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 GEELY AUTOMOBILE and Carnegie Clean into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between GEELY AUTOMOBILE and Carnegie Clean Energy, you can compare the effects of market volatilities on GEELY AUTOMOBILE and Carnegie Clean 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 GEELY AUTOMOBILE with a short position of Carnegie Clean. Check out your portfolio center. Please also check ongoing floating volatility patterns of GEELY AUTOMOBILE and Carnegie Clean.
Diversification Opportunities for GEELY AUTOMOBILE and Carnegie Clean
-0.01 | Correlation Coefficient |
Good diversification
The 3 months correlation between GEELY and Carnegie is -0.01. Overlapping area represents the amount of risk that can be diversified away by holding GEELY AUTOMOBILE and Carnegie Clean Energy in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Carnegie Clean Energy and GEELY AUTOMOBILE 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 GEELY AUTOMOBILE are associated (or correlated) with Carnegie Clean. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Carnegie Clean Energy has no effect on the direction of GEELY AUTOMOBILE i.e., GEELY AUTOMOBILE and Carnegie Clean go up and down completely randomly.
Pair Corralation between GEELY AUTOMOBILE and Carnegie Clean
Assuming the 90 days trading horizon GEELY AUTOMOBILE is expected to under-perform the Carnegie Clean. But the stock apears to be less risky and, when comparing its historical volatility, GEELY AUTOMOBILE is 1.78 times less risky than Carnegie Clean. The stock trades about -0.45 of its potential returns per unit of risk. The Carnegie Clean Energy is currently generating about 0.0 of returns per unit of risk over similar time horizon. If you would invest 2.12 in Carnegie Clean Energy on October 13, 2024 and sell it today you would lose (0.02) from holding Carnegie Clean Energy or give up 0.94% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
GEELY AUTOMOBILE vs. Carnegie Clean Energy
Performance |
| Timeline |
| GEELY AUTOMOBILE |
| Carnegie Clean Energy |
GEELY AUTOMOBILE and Carnegie Clean Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with GEELY AUTOMOBILE and Carnegie Clean
The main advantage of trading using opposite GEELY AUTOMOBILE and Carnegie Clean positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GEELY AUTOMOBILE position performs unexpectedly, Carnegie Clean 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 Carnegie Clean will offset losses from the drop in Carnegie Clean's long position.| GEELY AUTOMOBILE vs. HK Electric Investments | GEELY AUTOMOBILE vs. Virtus Investment Partners | GEELY AUTOMOBILE vs. CITY OFFICE REIT | GEELY AUTOMOBILE vs. British American Tobacco |
| Carnegie Clean vs. MOLSON RS BEVERAGE | Carnegie Clean vs. Mount Gibson Iron | Carnegie Clean vs. Nippon Steel | Carnegie Clean vs. MTY Food Group |
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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