Correlation Between Ningbo Fangzheng and Kingsignal Technology
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By analyzing existing cross correlation between Ningbo Fangzheng Automobile and Kingsignal Technology Co, you can compare the effects of market volatilities on Ningbo Fangzheng and Kingsignal 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 Ningbo Fangzheng with a short position of Kingsignal Technology. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ningbo Fangzheng and Kingsignal Technology.
Diversification Opportunities for Ningbo Fangzheng and Kingsignal Technology
0.9 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Ningbo and Kingsignal is 0.9. Overlapping area represents the amount of risk that can be diversified away by holding Ningbo Fangzheng Automobile and Kingsignal Technology Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kingsignal Technology and Ningbo Fangzheng 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 Ningbo Fangzheng Automobile are associated (or correlated) with Kingsignal Technology. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kingsignal Technology has no effect on the direction of Ningbo Fangzheng i.e., Ningbo Fangzheng and Kingsignal Technology go up and down completely randomly.
Pair Corralation between Ningbo Fangzheng and Kingsignal Technology
Assuming the 90 days trading horizon Ningbo Fangzheng Automobile is expected to generate 0.95 times more return on investment than Kingsignal Technology. However, Ningbo Fangzheng Automobile is 1.05 times less risky than Kingsignal Technology. It trades about 0.11 of its potential returns per unit of risk. Kingsignal Technology Co is currently generating about 0.01 per unit of risk. If you would invest 1,481 in Ningbo Fangzheng Automobile on August 30, 2024 and sell it today you would earn a total of 109.00 from holding Ningbo Fangzheng Automobile or generate 7.36% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Ningbo Fangzheng Automobile vs. Kingsignal Technology Co
Performance |
| Timeline |
| Ningbo Fangzheng Aut |
| Kingsignal Technology |
Ningbo Fangzheng and Kingsignal Technology Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Ningbo Fangzheng and Kingsignal Technology
The main advantage of trading using opposite Ningbo Fangzheng and Kingsignal Technology positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ningbo Fangzheng position performs unexpectedly, Kingsignal 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 Kingsignal Technology will offset losses from the drop in Kingsignal Technology's long position.| Ningbo Fangzheng vs. Innovative Medical Management | Ningbo Fangzheng vs. Shandong Homey Aquatic | Ningbo Fangzheng vs. Luolai Home Textile | Ningbo Fangzheng vs. Hunan Mendale Hometextile |
| Kingsignal Technology vs. China State Construction | Kingsignal Technology vs. Huafa Industrial Co | Kingsignal Technology vs. China International Capital | Kingsignal Technology vs. Kweichow Moutai Co |
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 Idea Optimizer module to use advanced portfolio builder with pre-computed micro ideas to build optimal portfolio .
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