Correlation Between Jiangsu Jiejie and Zhejiang Construction
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By analyzing existing cross correlation between Jiangsu Jiejie Microelectronics and Zhejiang Construction Investment, you can compare the effects of market volatilities on Jiangsu Jiejie and Zhejiang Construction 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 Jiangsu Jiejie with a short position of Zhejiang Construction. Check out your portfolio center. Please also check ongoing floating volatility patterns of Jiangsu Jiejie and Zhejiang Construction.
Diversification Opportunities for Jiangsu Jiejie and Zhejiang Construction
0.38 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Jiangsu and Zhejiang is 0.38. Overlapping area represents the amount of risk that can be diversified away by holding Jiangsu Jiejie Microelectronic and Zhejiang Construction Investme in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Zhejiang Construction and Jiangsu Jiejie 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 Jiangsu Jiejie Microelectronics are associated (or correlated) with Zhejiang Construction. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Zhejiang Construction has no effect on the direction of Jiangsu Jiejie i.e., Jiangsu Jiejie and Zhejiang Construction go up and down completely randomly.
Pair Corralation between Jiangsu Jiejie and Zhejiang Construction
Assuming the 90 days trading horizon Jiangsu Jiejie Microelectronics is expected to generate 1.74 times more return on investment than Zhejiang Construction. However, Jiangsu Jiejie is 1.74 times more volatile than Zhejiang Construction Investment. It trades about 0.19 of its potential returns per unit of risk. Zhejiang Construction Investment is currently generating about 0.01 per unit of risk. If you would invest 3,095 in Jiangsu Jiejie Microelectronics on November 4, 2024 and sell it today you would earn a total of 224.00 from holding Jiangsu Jiejie Microelectronics or generate 7.24% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Jiangsu Jiejie Microelectronic vs. Zhejiang Construction Investme
Performance |
| Timeline |
| Jiangsu Jiejie Micro |
| Zhejiang Construction |
Jiangsu Jiejie and Zhejiang Construction Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Jiangsu Jiejie and Zhejiang Construction
The main advantage of trading using opposite Jiangsu Jiejie and Zhejiang Construction positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Jiangsu Jiejie position performs unexpectedly, Zhejiang Construction 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 Zhejiang Construction will offset losses from the drop in Zhejiang Construction's long position.| Jiangsu Jiejie vs. Semiconductor Manufacturing Intl | Jiangsu Jiejie vs. Hubei Tech Semiconductors | Jiangsu Jiejie vs. Yuanjie Semiconductor Technology | Jiangsu Jiejie vs. Qingdao Foods Co |
| Zhejiang Construction vs. Shenzhen SDG Information | Zhejiang Construction vs. Xinjiang Baodi Mining | Zhejiang Construction vs. Western Metal Materials | Zhejiang Construction vs. YLZ Information Tech |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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