Correlation Between Shenzhen Coship and Ningbo Kangqiang
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By analyzing existing cross correlation between Shenzhen Coship Electronics and Ningbo Kangqiang Electronics, you can compare the effects of market volatilities on Shenzhen Coship and Ningbo Kangqiang 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 Shenzhen Coship with a short position of Ningbo Kangqiang. Check out your portfolio center. Please also check ongoing floating volatility patterns of Shenzhen Coship and Ningbo Kangqiang.
Diversification Opportunities for Shenzhen Coship and Ningbo Kangqiang
0.71 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Shenzhen and Ningbo is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding Shenzhen Coship Electronics and Ningbo Kangqiang Electronics in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ningbo Kangqiang Ele and Shenzhen Coship 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 Shenzhen Coship Electronics are associated (or correlated) with Ningbo Kangqiang. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ningbo Kangqiang Ele has no effect on the direction of Shenzhen Coship i.e., Shenzhen Coship and Ningbo Kangqiang go up and down completely randomly.
Pair Corralation between Shenzhen Coship and Ningbo Kangqiang
Assuming the 90 days trading horizon Shenzhen Coship is expected to generate 1.41 times less return on investment than Ningbo Kangqiang. But when comparing it to its historical volatility, Shenzhen Coship Electronics is 1.16 times less risky than Ningbo Kangqiang. It trades about 0.13 of its potential returns per unit of risk. Ningbo Kangqiang Electronics is currently generating about 0.16 of returns per unit of risk over similar time horizon. If you would invest 1,468 in Ningbo Kangqiang Electronics on October 14, 2024 and sell it today you would earn a total of 215.00 from holding Ningbo Kangqiang Electronics or generate 14.65% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Shenzhen Coship Electronics vs. Ningbo Kangqiang Electronics
Performance |
| Timeline |
| Shenzhen Coship Elec |
| Ningbo Kangqiang Ele |
Shenzhen Coship and Ningbo Kangqiang Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Shenzhen Coship and Ningbo Kangqiang
The main advantage of trading using opposite Shenzhen Coship and Ningbo Kangqiang positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Shenzhen Coship position performs unexpectedly, Ningbo Kangqiang 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 Ningbo Kangqiang will offset losses from the drop in Ningbo Kangqiang's long position.| Shenzhen Coship vs. Henan Shuanghui Investment | Shenzhen Coship vs. Vanfund Urban Investment | Shenzhen Coship vs. Xiandai Investment Co | Shenzhen Coship vs. Kunwu Jiuding Investment |
| Ningbo Kangqiang vs. Cloud Live Technology | Ningbo Kangqiang vs. Nanjing Putian Telecommunications | Ningbo Kangqiang vs. Tianjin Realty Development | Ningbo Kangqiang vs. Shenzhen Coship Electronics |
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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