Correlation Between Hengerda New and China Eastern
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By analyzing existing cross correlation between Hengerda New Materials and China Eastern Airlines, you can compare the effects of market volatilities on Hengerda New and China Eastern 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 Hengerda New with a short position of China Eastern. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hengerda New and China Eastern.
Diversification Opportunities for Hengerda New and China Eastern
0.64 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Hengerda and China is 0.64. Overlapping area represents the amount of risk that can be diversified away by holding Hengerda New Materials and China Eastern Airlines in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on China Eastern Airlines and Hengerda New 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 Hengerda New Materials are associated (or correlated) with China Eastern. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of China Eastern Airlines has no effect on the direction of Hengerda New i.e., Hengerda New and China Eastern go up and down completely randomly.
Pair Corralation between Hengerda New and China Eastern
Assuming the 90 days trading horizon Hengerda New Materials is expected to generate 1.0 times more return on investment than China Eastern. However, Hengerda New is 1.0 times more volatile than China Eastern Airlines. It trades about 0.27 of its potential returns per unit of risk. China Eastern Airlines is currently generating about 0.04 per unit of risk. If you would invest 2,472 in Hengerda New Materials on November 7, 2024 and sell it today you would earn a total of 260.00 from holding Hengerda New Materials or generate 10.52% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Hengerda New Materials vs. China Eastern Airlines
Performance |
| Timeline |
| Hengerda New Materials |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
| China Eastern Airlines |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
Hengerda New and China Eastern Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Hengerda New and China Eastern
The main advantage of trading using opposite Hengerda New and China Eastern positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hengerda New position performs unexpectedly, China Eastern 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 China Eastern will offset losses from the drop in China Eastern's long position.The idea behind Hengerda New Materials and China Eastern Airlines pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.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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