Correlation Between Clean Energy and Autohome ADR
Can any of the company-specific risk be diversified away by investing in both Clean Energy and Autohome ADR 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 Autohome ADR 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 Autohome ADR, you can compare the effects of market volatilities on Clean Energy and Autohome ADR 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 Autohome ADR. Check out your portfolio center. Please also check ongoing floating volatility patterns of Clean Energy and Autohome ADR.
Diversification Opportunities for Clean Energy and Autohome ADR
-0.12 | Correlation Coefficient |
Good diversification
The 3 months correlation between Clean and Autohome is -0.12. Overlapping area represents the amount of risk that can be diversified away by holding Clean Energy Fuels and Autohome ADR in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Autohome ADR 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 Autohome ADR. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Autohome ADR has no effect on the direction of Clean Energy i.e., Clean Energy and Autohome ADR go up and down completely randomly.
Pair Corralation between Clean Energy and Autohome ADR
Assuming the 90 days horizon Clean Energy is expected to generate 1.53 times less return on investment than Autohome ADR. In addition to that, Clean Energy is 1.44 times more volatile than Autohome ADR. It trades about 0.03 of its total potential returns per unit of risk. Autohome ADR is currently generating about 0.06 per unit of volatility. If you would invest 2,400 in Autohome ADR on September 12, 2024 and sell it today you would earn a total of 220.00 from holding Autohome ADR or generate 9.17% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Clean Energy Fuels vs. Autohome ADR
Performance |
Timeline |
Clean Energy Fuels |
Autohome ADR |
Clean Energy and Autohome ADR Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Clean Energy and Autohome ADR
The main advantage of trading using opposite Clean Energy and Autohome ADR positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Clean Energy position performs unexpectedly, Autohome ADR 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 Autohome ADR will offset losses from the drop in Autohome ADR's long position.Clean Energy vs. NISSAN CHEMICAL IND | Clean Energy vs. PRECISION DRILLING P | Clean Energy vs. Consolidated Communications Holdings | Clean Energy vs. Nissan Chemical Corp |
Autohome ADR vs. Tencent Holdings | Autohome ADR vs. Superior Plus Corp | Autohome ADR vs. SIVERS SEMICONDUCTORS AB | Autohome ADR vs. NorAm Drilling AS |
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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