Correlation Between Jinsanjiang (Zhaoqing) and Chengdu Xuguang
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By analyzing existing cross correlation between Jinsanjiang Silicon Material and Chengdu Xuguang Electronics, you can compare the effects of market volatilities on Jinsanjiang (Zhaoqing) and Chengdu Xuguang 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 Jinsanjiang (Zhaoqing) with a short position of Chengdu Xuguang. Check out your portfolio center. Please also check ongoing floating volatility patterns of Jinsanjiang (Zhaoqing) and Chengdu Xuguang.
Diversification Opportunities for Jinsanjiang (Zhaoqing) and Chengdu Xuguang
0.16 | Correlation Coefficient |
Average diversification
The 3 months correlation between Jinsanjiang and Chengdu is 0.16. Overlapping area represents the amount of risk that can be diversified away by holding Jinsanjiang Silicon Material and Chengdu Xuguang Electronics in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Chengdu Xuguang Elec and Jinsanjiang (Zhaoqing) 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 Jinsanjiang Silicon Material are associated (or correlated) with Chengdu Xuguang. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Chengdu Xuguang Elec has no effect on the direction of Jinsanjiang (Zhaoqing) i.e., Jinsanjiang (Zhaoqing) and Chengdu Xuguang go up and down completely randomly.
Pair Corralation between Jinsanjiang (Zhaoqing) and Chengdu Xuguang
Assuming the 90 days trading horizon Jinsanjiang (Zhaoqing) is expected to generate 13.98 times less return on investment than Chengdu Xuguang. In addition to that, Jinsanjiang (Zhaoqing) is 1.11 times more volatile than Chengdu Xuguang Electronics. It trades about 0.01 of its total potential returns per unit of risk. Chengdu Xuguang Electronics is currently generating about 0.08 per unit of volatility. If you would invest 762.00 in Chengdu Xuguang Electronics on December 28, 2024 and sell it today you would earn a total of 91.00 from holding Chengdu Xuguang Electronics or generate 11.94% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 98.28% |
Values | Daily Returns |
Jinsanjiang Silicon Material vs. Chengdu Xuguang Electronics
Performance |
Timeline |
Jinsanjiang (Zhaoqing) |
Chengdu Xuguang Elec |
Jinsanjiang (Zhaoqing) and Chengdu Xuguang Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Jinsanjiang (Zhaoqing) and Chengdu Xuguang
The main advantage of trading using opposite Jinsanjiang (Zhaoqing) and Chengdu Xuguang positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Jinsanjiang (Zhaoqing) position performs unexpectedly, Chengdu Xuguang 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 Chengdu Xuguang will offset losses from the drop in Chengdu Xuguang's long position.Jinsanjiang (Zhaoqing) vs. Air China Ltd | Jinsanjiang (Zhaoqing) vs. GigaDevice SemiconductorBeiji | Jinsanjiang (Zhaoqing) vs. Hubei Tech Semiconductors | Jinsanjiang (Zhaoqing) vs. Luyin Investment Group |
Chengdu Xuguang vs. Epoxy Base Electronic | Chengdu Xuguang vs. Miracll Chemicals Co | Chengdu Xuguang vs. Huawen Media Investment | Chengdu Xuguang vs. Zhongrun Resources 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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