Correlation Between Jinli Group and Hung Sheng
Can any of the company-specific risk be diversified away by investing in both Jinli Group and Hung Sheng 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 Jinli Group and Hung Sheng into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Jinli Group Holdings and Hung Sheng Construction, you can compare the effects of market volatilities on Jinli Group and Hung Sheng 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 Jinli Group with a short position of Hung Sheng. Check out your portfolio center. Please also check ongoing floating volatility patterns of Jinli Group and Hung Sheng.
Diversification Opportunities for Jinli Group and Hung Sheng
0.38 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Jinli and Hung is 0.38. Overlapping area represents the amount of risk that can be diversified away by holding Jinli Group Holdings and Hung Sheng Construction in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hung Sheng Construction and Jinli Group 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 Jinli Group Holdings are associated (or correlated) with Hung Sheng. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hung Sheng Construction has no effect on the direction of Jinli Group i.e., Jinli Group and Hung Sheng go up and down completely randomly.
Pair Corralation between Jinli Group and Hung Sheng
Assuming the 90 days trading horizon Jinli Group Holdings is expected to generate 1.26 times more return on investment than Hung Sheng. However, Jinli Group is 1.26 times more volatile than Hung Sheng Construction. It trades about 0.1 of its potential returns per unit of risk. Hung Sheng Construction is currently generating about 0.0 per unit of risk. If you would invest 993.00 in Jinli Group Holdings on September 1, 2024 and sell it today you would earn a total of 297.00 from holding Jinli Group Holdings or generate 29.91% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 99.22% |
| Values | Daily Returns |
Jinli Group Holdings vs. Hung Sheng Construction
Performance |
| Timeline |
| Jinli Group Holdings |
| Hung Sheng Construction |
Jinli Group and Hung Sheng Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Jinli Group and Hung Sheng
The main advantage of trading using opposite Jinli Group and Hung Sheng positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Jinli Group position performs unexpectedly, Hung Sheng 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 Hung Sheng will offset losses from the drop in Hung Sheng's long position.| Jinli Group vs. Shui Mu International Co | Jinli Group vs. Les Enphants Co | Jinli Group vs. Victory New Materials | Jinli Group vs. Shinih Enterprise Co |
| Hung Sheng vs. Ruentex Development Co | Hung Sheng vs. CTCI Corp | Hung Sheng vs. Information Technology Total | Hung Sheng vs. Ennoconn 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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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