Correlation Between Beijing HuaYuanYiTong and Sinofibers Technology
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By analyzing existing cross correlation between Beijing HuaYuanYiTong Thermal and Sinofibers Technology Co, you can compare the effects of market volatilities on Beijing HuaYuanYiTong and Sinofibers Technology 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 Beijing HuaYuanYiTong with a short position of Sinofibers Technology. Check out your portfolio center. Please also check ongoing floating volatility patterns of Beijing HuaYuanYiTong and Sinofibers Technology.
Diversification Opportunities for Beijing HuaYuanYiTong and Sinofibers Technology
0.77 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Beijing and Sinofibers is 0.77. Overlapping area represents the amount of risk that can be diversified away by holding Beijing HuaYuanYiTong Thermal and Sinofibers Technology Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Sinofibers Technology and Beijing HuaYuanYiTong 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 Beijing HuaYuanYiTong Thermal are associated (or correlated) with Sinofibers Technology. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Sinofibers Technology has no effect on the direction of Beijing HuaYuanYiTong i.e., Beijing HuaYuanYiTong and Sinofibers Technology go up and down completely randomly.
Pair Corralation between Beijing HuaYuanYiTong and Sinofibers Technology
Assuming the 90 days trading horizon Beijing HuaYuanYiTong Thermal is expected to under-perform the Sinofibers Technology. In addition to that, Beijing HuaYuanYiTong is 1.5 times more volatile than Sinofibers Technology Co. It trades about -0.06 of its total potential returns per unit of risk. Sinofibers Technology Co is currently generating about 0.07 per unit of volatility. If you would invest 2,735 in Sinofibers Technology Co on September 23, 2024 and sell it today you would earn a total of 57.00 from holding Sinofibers Technology Co or generate 2.08% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Beijing HuaYuanYiTong Thermal vs. Sinofibers Technology Co
Performance |
Timeline |
Beijing HuaYuanYiTong |
Sinofibers Technology |
Beijing HuaYuanYiTong and Sinofibers Technology Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Beijing HuaYuanYiTong and Sinofibers Technology
The main advantage of trading using opposite Beijing HuaYuanYiTong and Sinofibers Technology positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Beijing HuaYuanYiTong position performs unexpectedly, Sinofibers Technology 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 Sinofibers Technology will offset losses from the drop in Sinofibers Technology's long position.Beijing HuaYuanYiTong vs. Ping An Insurance | Beijing HuaYuanYiTong vs. Anhui Deli Household | Beijing HuaYuanYiTong vs. Shandong Longquan Pipeline | Beijing HuaYuanYiTong vs. Hua Xia Bank |
Sinofibers Technology vs. Zijin Mining Group | Sinofibers Technology vs. Wanhua Chemical Group | Sinofibers Technology vs. Baoshan Iron Steel | Sinofibers Technology vs. Shandong Gold Mining |
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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